The DOI matches its Crossref record; 78 of the 78 references it cites were found in a registry or an index; none of the 26 sources its claims cite is checked for support yet.
A "SMART" Design for Building Individualized Treatment Sequences
Open accessAbstract
Interventions often involve a sequence of decisions. For example, clinicians frequently adapt the intervention to an individual's outcomes. Altering the intensity and type of intervention over time is crucial for many reasons, such as to obtain improvement if the individual is not responding or to reduce costs and burden when intensive treatment is no longer necessary. Adaptive interventions utilize individual variables (severity, preferences) to adapt the intervention and then dynamically utilize individual outcomes (response to treatment, adherence) to readapt the intervention. The Sequential Multiple Assignment Randomized Trial (SMART) provides high-quality data that can be used to construct adaptive interventions. We review the SMART and highlight its advantages in constructing and revising adaptive interventions as compared to alternative experimental designs. Selected examples of SMART studies are described and compared. A data analysis method is provided and illustrated using data from the Extending Treatment Effectiveness of Naltrexone SMART study.
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Claims the paper makes
41 Own interpretation · 17 Not checked yet · 10 No basis given · 5 Own method · 4 Own result
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The results reported in Table 6 also indicate that the adaptive interventions in comparisons 3 and 4 are not significantly different in terms of achieving drinking abstinence at the end of stage two [estimated logitP(Y = 1) = −0.61; −0.39, ns, for comparison 3 and 4, respectively].”
§ A “SMART” Design for Building Individualized Treatment Sequences > THE EXTEND TRIAL EXAMPLE > Results
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption: The missing data are missing at random or otherwise appropriately handled by multiple imputation, so that the imputation yields valid estimates.
- Rests on an assumption: The logistic regression model is correctly specified for estimating the effects of the adaptive interventions.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The results reported in Table 6 indicate that the adaptive interventions in comparisons 1 and 2 are significantly different in terms of achieving drinking abstinence at the end of stage two [estimated logit P(Y = 1) = −1.17; −0.96, p < 0.05, for comparison 1 and 2, respectively].”
§ A “SMART” Design for Building Individualized Treatment Sequences > THE EXTEND TRIAL EXAMPLE > Results
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption: The missing data are missing at random or otherwise appropriately handled by multiple imputation, so that the imputation yields valid estimates.
- Rests on an assumption: The logistic regression model is correctly specified for estimating the effects of the adaptive interventions.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“These advantages are (a) increased validity of analyses aimed at discovering when the effect of one intervention is enhanced by subsequent or prior interventions, (b) increased validity of analyses aimed at discovering useful tailoring variables, and (c) increased ability to reduce the impact of cohort effects.”
§ A “SMART” Design for Building Individualized Treatment Sequences > THE SEQUENTIAL MULTIPLE ASSIGNMENT RANDOMIZED TRIAL > Comparison to Alternative Experimental Designs
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption: The best intervention option for a patient varies with the values of the tailoring variables.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Specifically, investigators can collect information on candidate tailoring variables that are outcomes of the initial intervention and assess their usefulness in matching subsequent intervention options to participants.”
§ A “SMART” Design for Building Individualized Treatment Sequences > THE SEQUENTIAL MULTIPLE ASSIGNMENT RANDOMIZED TRIAL > Why Run a SMART Trial?
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption: The best intervention option for a patient varies with the values of the tailoring variables.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Other questions may concern the comparison of adaptive interventions that are embedded in the SMART trial, such as the differences between the eight adaptive interventions specified in Table 2.”
§ A “SMART” Design for Building Individualized Treatment Sequences > THE SEQUENTIAL MULTIPLE ASSIGNMENT RANDOMIZED TRIAL > Why Run a SMART Trial?
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The Sequential Multiple Assignment Randomized Trial (SMART)provides high-quality data that can be used to construct adaptive interventions.”
§ A “SMART” Design for Building Individualized Treatment Sequences > Abstract
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Data from a SMART design can be used to address many interesting questions that are useful for the construction of high-quality adaptive intervention. These questions may concern the comparison of different intervention options at different stages of the intervention.”
§ A “SMART” Design for Building Individualized Treatment Sequences > THE SEQUENTIAL MULTIPLE ASSIGNMENT RANDOMIZED TRIAL > Why Run a SMART Trial?
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“These advantages are (a) increased validity of analyses aimed at discovering when the effect of one intervention is enhanced by subsequent or prior interventions, (b) increased validity of analyses aimed at discovering useful tailoring variables, and (c) increased ability to reduce the impact of cohort effects.”
§ A “SMART” Design for Building Individualized Treatment Sequences > THE SEQUENTIAL MULTIPLE ASSIGNMENT RANDOMIZED TRIAL > Comparison to Alternative Experimental Designs
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
None of the sources cited for this claim have been checked yet.
In the paper
“As in standard intervention trials, the randomization allows scientists to make valid causal inferences concerning the relative effectiveness of the intervention options without having to make unverifiable assumptions (Rubin 1974, 2007).”
§ A “SMART” Design for Building Individualized Treatment Sequences > THE SEQUENTIAL MULTIPLE ASSIGNMENT RANDOMIZED TRIAL > What Is the SMART Design?
What the sources say
- Not checked yetcites Rubin 1974
- Not checked yetcites Rubin 2007
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
In the paper
“For example, in secondary data analyses of the ADHD study, Nahum-Shani et al. (2011a,b) found evidence that children’s adherence to the first-stage intervention could be used to individualize the second-stage intervention.”
§ A “SMART” Design for Building Individualized Treatment Sequences > THE SEQUENTIAL MULTIPLE ASSIGNMENT RANDOMIZED TRIAL > Comparison to Alternative Experimental Designs
What the sources say
- Not checked yetcites Nahum-Shani et al. (2011a,b)
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- It may state two separate claims as one. 17
- Probably not a substantial claim. 12
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The results reported in Table 5 indicate that the coefficients of A1, and A1*A2nr are significantly different from zero (β̂1 = 0.39; β̂5 = −0.14, p < 0.05, respectively), and the coefficient of A2R is marginally significant (β̂2 = −0.24, p = 0.10).”
§ A “SMART” Design for Building Individualized Treatment Sequences > THE EXTEND TRIAL EXAMPLE > Results
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Rests on an assumption: The missing data are missing at random or otherwise appropriately handled by multiple imputation, so that the imputation yields valid estimates.
- Rests on an assumption: The logistic regression model is correctly specified for estimating the effects of the adaptive interventions.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Notice that the regression coefficient for A2NR is not significantly different from zero (β̂3 = 0.02), meaning that on average, there is no difference between the two treatment options for nonresponders in achieving abstinence.”
§ A “SMART” Design for Building Individualized Treatment Sequences > THE EXTEND TRIAL EXAMPLE > Results
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Rests on an assumption: The missing data are missing at random or otherwise appropriately handled by multiple imputation, so that the imputation yields valid estimates.
- Rests on an assumption: The logistic regression model is correctly specified for estimating the effects of the adaptive interventions.
None of the sources cited for this claim have been checked yet.
In the paper
“This approach is based on the notion that patients differ in their responses to interventions: In order for an intervention to be most effective, it should be individualized and repeatedly adapted over time to individual progress.”
§ A “SMART” Design for Building Individualized Treatment Sequences > OVERVIEW
What the sources say
- Not checked yetcites Bierman et al. 2006
- Not checked yetcites Marlowe et al. 2008
- Not checked yetcites McKay 2005
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“Evidence-based practice … is not a specific treatment or a set of treatments, but rather an orientation or a value system that relies on evidence to guide the entire treatment process. Thus, a critical element of evidence-based care is periodic assessment to gauge whether the treatment selected initially is in fact proving helpful.”
§ A “SMART” Design for Building Individualized Treatment Sequences > OVERVIEW
What the sources say
- Not checked yetcites Weisz et al. (2004)
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Because SMARTs are used to develop adaptive interventions as opposed to confirming that a particular adaptive intervention is better than control, SMARTs should be followed by a randomized confirmatory trial in which the developed adaptive intervention is compared to an appropriate alternative.”
§ A “SMART” Design for Building Individualized Treatment Sequences > THE SEQUENTIAL MULTIPLE ASSIGNMENT RANDOMIZED TRIAL > What Is the SMART Design?
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
In the paper
“The conceptual advantages of adaptive interventions over a fixed-intervention approach (in which all patients are offered the same type or dosage of the intervention) have long been recognized by behavioral scientists.”
§ A “SMART” Design for Building Individualized Treatment Sequences > OVERVIEW
What the sources say
- Not checked yetcites Weisz et al. (2004)
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In contrast, in a SMART study the clinical team can prospectively manipulate and record the type and intensity of the intervention during the initial stage.”
§ A “SMART” Design for Building Individualized Treatment Sequences > THE SEQUENTIAL MULTIPLE ASSIGNMENT RANDOMIZED TRIAL > Comparison to Alternative Experimental Designs
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“However, the quality and validity of these recall measures might be lower relative to the more proximally measured adherence collected during the SMART study.”
§ A “SMART” Design for Building Individualized Treatment Sequences > THE SEQUENTIAL MULTIPLE ASSIGNMENT RANDOMIZED TRIAL > Comparison to Alternative Experimental Designs
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Forty-one participants dropped out at the second stage.”
§ A “SMART” Design for Building Individualized Treatment Sequences > THE EXTEND TRIAL EXAMPLE > Sample
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Secondary research questions typically concern (a) the comparison of second-stage intervention options, (b) the comparison of embedded adaptive interventions, and (c) the usefulness of candidate tailoring variables (beyond the tailoring variable already embedded in the design).”
§ A “SMART” Design for Building Individualized Treatment Sequences > EXAMPLES OF SMART STUDIES > Comparison of SMART Studies
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The advantages of SMART designs over a randomized comparison of the fully formed adaptive intervention with a control are related to the fact that the SMART design enables clinical scientists to open the “black box” using randomized comparisons. In contrast, the randomized two-group comparison approach is designed with a very different goal, that is, to provide information on whether the adaptive”
§ A “SMART” Design for Building Individualized Treatment Sequences > THE SEQUENTIAL MULTIPLE ASSIGNMENT RANDOMIZED TRIAL > Comparison to Alternative Experimental Designs
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“The effective sample size for the randomized study was 253 participants.”
§ A “SMART” Design for Building Individualized Treatment Sequences > THE EXTEND TRIAL EXAMPLE > Sample
plainn = 253- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“In the CCNIA study, only a subset of the nonresponding children is rerandomized. Specifically, children who do not respond to JAE+EMT are randomly assigned either to receive intensified JAE+EMT or to switch to JAE+AAC.”
§ A “SMART” Design for Building Individualized Treatment Sequences > EXAMPLES OF SMART STUDIES > Comparison of SMART Studies
What the sources say
- Not checked yetcites Kasari 2009a,b
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“In the ExTENd example, this would be the main effect of NTX+TDM versus NTX alone for responding participants and the main effect of CBI+MM+NTX versus CBI+MM+placebo for nonresponding participants.”
§ A “SMART” Design for Building Individualized Treatment Sequences > USING DATA FROM A SMART TO INFORM THE CONSTRUCTION OF AN OPTIMIZED ADAPTIVE INTERVENTION
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Only three adaptive interventions are embedded in the CCNIA SMART design, in which only two critical decisions were addressed by randomization: one concerning the frontline intervention and the other concerning the rescue intervention for nonresponders to one of the frontline interventions.”
§ A “SMART” Design for Building Individualized Treatment Sequences > EXAMPLES OF SMART STUDIES > Comparison of SMART Studies
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“Nahum-Shani et al. (2011a,b) provide analysis methods for addressing primary and secondary research questions using data from SMART studies.”
§ A “SMART” Design for Building Individualized Treatment Sequences > USING DATA FROM A SMART TO INFORM THE CONSTRUCTION OF AN OPTIMIZED ADAPTIVE INTERVENTION
What the sources say
- Not checked yetcites Nahum-Shani et al. (2011a,b)
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In a randomized two-group trial, there is no randomization to different second-stage interventions, and thus again analyses must depend on variation due to nonadherence and implementation infidelity.”
§ A “SMART” Design for Building Individualized Treatment Sequences > THE SEQUENTIAL MULTIPLE ASSIGNMENT RANDOMIZED TRIAL > Comparison to Alternative Experimental Designs
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Forty-nine participants dropped out prior to experiencing two heavy drinking days and thus experienced no effect of the first-stage randomization.”
§ A “SMART” Design for Building Individualized Treatment Sequences > THE EXTEND TRIAL EXAMPLE > Sample
plainn = 9- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The RBT SMART study, on the other hand, contrasts variants of the same intervention (RBT) and hence involves only one treatment modality.”
§ A “SMART” Design for Building Individualized Treatment Sequences > EXAMPLES OF SMART STUDIES > Comparison of SMART Studies
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In SMART designs, the intervention offered to a specific participant is adapted on the basis of information obtained on this participant (e.g., the participant’s signs of early response or level of adherence to the initial interventions), whereas in adaptive experimental designs, the randomization probabilities are adapted on the basis of information obtained from other participants in prior”
§ A “SMART” Design for Building Individualized Treatment Sequences > THE SEQUENTIAL MULTIPLE ASSIGNMENT RANDOMIZED TRIAL > The SMART Experimental Design Versus the Adaptive Experimental Design
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Finally, eight adaptive interventions are embedded in the RBT and the ExTENd SMART designs, in which five critical decisions were addressed by randomizations.”
§ A “SMART” Design for Building Individualized Treatment Sequences > EXAMPLES OF SMART STUDIES > Comparison of SMART Studies
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The number of treatment modalities utilized in SMART studies depends on the scientific evidence and the research questions at hand.”
§ A “SMART” Design for Building Individualized Treatment Sequences > EXAMPLES OF SMART STUDIES > Comparison of SMART Studies
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Only three additional participants dropped out during the first-stage treatment; the data from these participants were deleted, leaving a sample size of 250 participants.”
§ A “SMART” Design for Building Individualized Treatment Sequences > THE EXTEND TRIAL EXAMPLE > Sample
plainn = 3- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“To accommodate the resulting missing data, multiple imputation was used in the analyses below.”
§ A “SMART” Design for Building Individualized Treatment Sequences > THE EXTEND TRIAL EXAMPLE > Sample
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“These results indicate that we are to provide nonresponders with the more-intensive second-stage intervention (CBI+MM+NTX); it is less clear whether we should begin with the lenient or the stringent definition of nonresponse.”
§ A “SMART” Design for Building Individualized Treatment Sequences > THE EXTEND TRIAL EXAMPLE > Results
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
- Rests on an assumption: The missing data are missing at random or otherwise appropriately handled by multiple imputation, so that the imputation yields valid estimates.
- Rests on an assumption: The logistic regression model is correctly specified for estimating the effects of the adaptive interventions.
In the paper
“The missing data in this data set are handled with multiple imputation using the R mice procedure (van Buuren & Groothuis-Oudshoorn 2010).”
§ A “SMART” Design for Building Individualized Treatment Sequences > THE EXTEND TRIAL EXAMPLE > Results
What the sources say
- Not checked yetcites van Buuren & Groothuis-Oudshoorn 2010
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Each participant is consistent with two adaptive interventions (i.e., the observed primary outcome of each participant is used in estimating the average primary outcome of two adaptive interventions; for more details, see Nahum-Shani et al. 2011a).”
§ A “SMART” Design for Building Individualized Treatment Sequences > THE EXTEND TRIAL EXAMPLE > Sample
What the sources say
- Not checked yetcites Nahum-Shani et al. 2011a
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper relies on this without support.
The best intervention option for a patient varies with the values of the tailoring variables.
“The logic is that the best intervention option for patients varies according to different values of the tailoring variables.”
The paper relies on this without support.
Comorbid conditions require decisions about which disorder to treat first or whether to treat multiple disorders at once.
“A third reason for considering an adaptive intervention is the presence of, or evolving, comorbidities (e.g., comorbid HIV infection and substance use, depression and alcoholism). Comorbid conditions require decisions regarding which disorder should be treated first or whether multiple disorders should be treated simultaneously.”
The paper relies on this without support.
The high cost of intensive interventions, along with possible burden and side effects, justifies developing interventions that reduce intensity when possible.
“Fifth, the high cost of intensive interventions combined with possible burden and/or side effects motivate the development of interventions in which the intensity of the treatment is reduced when possible.”
The paper relies on this without support.
Interest among intervention scientists in experimental designs that directly inform intervention adaptation has grown in recent years.
“In recent years, intervention scientists have become increasingly interested in experimental designs that explicitly inform the adaptive aspects of the intervention.”
The paper relies on this without support.
The missing data are missing at random or otherwise appropriately handled by multiple imputation, so that the imputation yields valid estimates.
“To accommodate the resulting missing data, multiple imputation was used in the analyses below.”
“The missing data in this data set are handled with multiple imputation using the R mice procedure (van Buuren & Groothuis-Oudshoorn 2010).”
The paper relies on this without support.
The logistic regression model is correctly specified for estimating the effects of the adaptive interventions.
“The logistic regression model below can be used to compare the eight adaptive interventions embedded in the ExTENd trial:”
“(1)logitP(Y=1|A1,A2R,A2NR,O1)=β0+β1*A1+β2*A2R+β3*A2NR+β4*A1*A2R+β5*A1*A2NR+γTO1.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“The adaptive intervention that a SMART design produces can be incorporated into clinical practice more naturally and seamlessly than the findings of a fixed-intervention study [53, 54, 62].”
From A Sequential Multiple Assignment Randomized Trial (SMART) study of medication and CBT sequencing in the treatment of pediatric anxiety disorders (2021) · cites this paper as [53]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“Different SMART designs are suitable for addressing different types of scientific questions [21,23].”
From Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research (2014) · cites this paper as [23]
The cited source says what the claim attributes to it.
In the citing paper
“Findings of the sequential randomization aspect of the SMART design during treatment can inform clinician decisions about treatment sequencing based on the individual patient’s response to the intervention currently in use, further supporting personalized treatment [53, 54].”
From A Sequential Multiple Assignment Randomized Trial (SMART) study of medication and CBT sequencing in the treatment of pediatric anxiety disorders (2021) · cites this paper as [53]
The cited source says what the claim attributes to it.
In the citing paper
“making them ideal for developing an adaptive intervention that optimizes outcomes based on patient treatment history [51–54].”
From A Sequential Multiple Assignment Randomized Trial (SMART) study of medication and CBT sequencing in the treatment of pediatric anxiety disorders (2021) · cites this paper as [53]
In the citing paper
“Lei et al. [23] describe the rationale and scientific questions addressed by four different SMART studies either recently completed or underway in autism, attention-deficit/hyperactivity disorder (ADHD), and for various substance use disorders.”
From Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research (2014) · cites this paper as [23]
In the citing paper
“The Sequential Multiple Assignment Randomized Implementation Trial (SMART) implementation design is a special case of the factorial experiment (32, 67, 78) involving multistage randomizations where the site-level implementation process can be modified if unsuccessful.”
From An Overview of Research and Evaluation Designs for Dissemination and Implementation (2017) · cites this paper as [67]
In the citing paper
“the likelihood of response of these syndromes to the introduction of new antidepressants is very variable [29-33].”
From The Deceptive Manifestations of Treatment Resistance in Depression: A New Look at the Problem (2020) · cites this paper as [33]
In the citing paper
“Even with slow tapering, the likelihood of withdrawal syndromes and persistent postwithdrawal disorders and symptoms is very high”
From The Deceptive Manifestations of Treatment Resistance in Depression: A New Look at the Problem (2020) · cites this paper as [33]
Citations
Cites
mice: Multivariate Imputation by Chained Equations in R
Buuren, S. V., & Groothuis-Oudshoorn, K. (2011) · Journal of Statistical Software · doi:10.18637/jss.v045.i03 · Cited by 13,870
Estimating causal effects of treatments in randomized and nonrandomized studies
Rubin, D. B. (1974) · Journal of Educational Psychology · doi:10.1037/h0037350 · Cited by 9,436
Rush, A. J., Trivedi, M. H., Wisniewski, S. R., Nierenberg, A. A., Stewart, J. W., Warden, D., Niederehe, G., Thase, M. E., Lavori, P. W., Lebowitz, B. D., et al. (2006) · American Journal of Psychiatry · doi:10.1176/ajp.2006.163.11.1905 · Cited by 5,643 · cited 1×
“Other precursors of SMART include the CATIE trial of treatments for patients with Alzheimer’s disease (Schneider et al. 2003) and STAR∗D for treatment of depression (Rush et al. 2004, 2006).”
MethodMarginal Structural Models and Causal Inference in Epidemiology
Robins, J. M., Hernán, M. Á., & Brumback, B. (2000) · Epidemiology · doi:10.1097/00001648-200009000-00011 · Cited by 5,581
Drug Dependence, a Chronic Medical Illness
McLellan, A. T., Lewis, D. C., O'Brien, C. P., & Kleber, H. D. (2000) · JAMA · doi:10.1001/jama.284.13.1689 · Cited by 2,622 · cited 1×
“For example, in the treatment of substance abuse, patients are at high risk for relapse even after achieving an acute response (McKay 2009, McKay et al. 2010, McLellan 2002, McLellan et al. 2000).”
BackgroundRobins, J. (1986) · Mathematical Modelling · doi:10.1016/0270-0255(86)90088-6 · Cited by 2,451
Group sequential methods in the design and analysis of clinical trials
POCOCK, S. J. (1977) · Biometrika · doi:10.1093/biomet/64.2.191 · Cited by 1,831
Hernán, M. Á., Brumback, B., & Robins, J. M. (2000) · Epidemiology · doi:10.1097/00001648-200009000-00012 · Cited by 1,772
Pliszka, S. (2007) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1097/chi.0b013e318054e724 · Cited by 1,765
Teacher Ratings of DSM-III-R Symptoms for the Disruptive Behavior Disorders
Pelham, W. E., Gnagy, E. M., Greenslade, K. E., & Milich, R. S. (1992) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1097/00004583-199203000-00006 · Cited by 1,315
Sequenced treatment alternatives to relieve depression (STAR*D): Rationale and design
Rush, A. J., Fava, M., Wisniewski, S. R., Lavori, P. W., Trivedi, M. H., Sackeim, H. A., Thase, M. E., Nierenberg, A. A., Quitkin, F. M., Kashner, T. M., et al. (2004) · Controlled Clinical Trials · doi:10.1016/s0197-2456(03)00112-0 · Cited by 1,076
Rubin, D. B. (2007) · Statistics in Medicine · doi:10.1002/sim.2739 · Cited by 1,047
Kasari, C., Freeman, S., & Paparella, T. (2006) · Journal of Child Psychology and Psychiatry · doi:10.1111/j.1469-7610.2005.01567.x · Cited by 951
Evidence-based psychosocial treatments for attention-deficit/hyperactivity disorder
Pelham, W. E., & Fabiano, G. A. (2008) · Journal of Clinical Child & Adolescent Psychology · doi:10.1080/15374410701818681 · Cited by 917
An experimental design for the development of adaptive treatment strategies
Murphy, S. A. (2005) · Statistics in Medicine · doi:10.1002/sim.2022 · Cited by 746
Self-citationFabiano, G. A., Pelham, W. E., Waschbusch, D. A., Gnagy, E. M., Lahey, B. B., Chronis, A. M., Onyango, A. N., Kipp, H., Lopez-Williams, A., & Burrows-MacLean, L. D. (2006) · Journal of Clinical Child & Adolescent Psychology · doi:10.1207/s15374424jccp3503_3 · Cited by 689
Stroup, T., Mcevoy, J., Swartz, M., Byerly, M., Glick, I., Cañive, J., McGee, M., Simpson, G., Stevens, M., & Lieberman, J. (2003) · Schizophrenia bulletin · doi:10.1093/oxfordjournals.schbul.a006986 · Cited by 647
A Conceptual Framework for Adaptive Preventive Interventions
Collins, L. M., Murphy, S. A., & Bierman, K. L. (2004) · Prevention Science · doi:10.1023/b:prev.0000037641.26017.00 · Cited by 608
Self-citationLanguage outcome in autism: randomized comparison of joint attention and play interventions
Kasari, C., Paparella, T., Freeman, S., & Jahromi, L. B. (2008) · Journal of Consulting and Clinical Psychology · doi:10.1037/0022-006x.76.1.125 · Cited by 592
Patterns of growth in verbal abilities among children with autism spectrum disorder.
Anderson, D. K., Lord, C., Risi, S., DiLavore, P. S., Shulman, C., Thurm, A., Welch, K., & Pickles, A. (2007) · Journal of Consulting and Clinical Psychology · doi:10.1037/0022-006x.75.4.594 · Cited by 553
Crits-Christoph, P. F. (1999) · Archives of General Psychiatry · doi:10.1001/archpsyc.56.6.493 · Cited by 497
Adaptive design methods in clinical trials–a review
Chow, S.-C., & Chang, M. (2008) · Orphanet Journal of Rare Diseases · doi:10.1186/1750-1172-3-11 · Cited by 482
Stone, R. M., Berg, D. T., George, S. L., Dodge, R. K., Paciucci, P. A., Schulman, P., Lee, E. J., Moore, J. O., Powell, B. L., & Schiffer, C. A. (1995) · New England Journal of Medicine · doi:10.1056/nejm199506223322503 · Cited by 447
Treatment of language disorders in children
McCauley, R. J., & Fey, M. E. (2006) · Cited by 397
Marginal Mean Models for Dynamic Regimes
Murphy, S. A., van der Laan, M. J., Robins, J. M., & Conduct Problems Prevention Research Group (2001) · Journal of the American Statistical Association · doi:10.1198/016214501753382327 · Cited by 393
Self-citationThe development of symbol-infused joint engagement
Adamson, L. B., Bakeman, R., & Deckner, D. F. (2004) · Child Development · doi:10.1111/j.1467-8624.2004.00732.x · Cited by 370
The Life Course Perspective on Drug Use
Hser, Y., Longshore, D. L., & Anglin, M. D. (2007) · Evaluation Review · doi:10.1177/0193841x07307316 · Cited by 360
Stepped care as a heuristic approach to the treatment of alcohol problems.
Sobell, M. B., & Sobell, L. C. (2000) · Journal of Consulting and Clinical Psychology · doi:10.1037/0022-006x.68.4.573 · Cited by 345
Hernán, M. Á., Brumback, B., & Robins, J. M. (2002) · Statistics in Medicine · doi:10.1002/sim.1144 · Cited by 335
Have we evaluated addiction treatment correctly? Implications from a chronic care perspective
McLellan, A. T. (2002) · Addiction · doi:10.1046/j.1360-0443.2002.00127.x · Cited by 307
Experimental design and primary data analysis methods for comparing adaptive interventions.
Nahum-Shani, I., Qian, M., Almirall, D., Pelham, W. E., Gnagy, B., Fabiano, G. A., Waxmonsky, J. G., Yu, J., & Murphy, S. A. (2012) · Psychological Methods · doi:10.1037/a0029372 · Cited by 298
Self-citationContinuing care research: What we have learned and where we are going
McKay, J. R. (2009) · Journal of Substance Abuse Treatment · doi:10.1016/j.jsat.2008.10.004 · Cited by 249
Dynamic treatment regimes: practical design considerations
Lavori, P. W., & Dawson, R. (2004) · Clinical Trials · doi:10.1191/1740774s04cn002oa · Cited by 229
A Design for Testing Clinical Strategies: Biased Adaptive Within-Subject Randomization
Lavori, P. W., & Dawson, R. (2000) · Journal of the Royal Statistical Society Series A (Statistics in Society) · doi:10.1111/1467-985x.00154 · Cited by 228
Robins, J. M. (1987) · Computers & Mathematics with Applications · doi:10.1016/0898-1221(87)90238-0 · Cited by 213
Is there a case for extended interventions for alcohol and drug use disorders?
McKay, J. R. (2005) · Addiction · doi:10.1111/j.1360-0443.2005.01208.x · Cited by 211
Developing adaptive treatment strategies in substance abuse research
Murphy, S. A., Lynch, K. G., Oslin, D., McKay, J. R., & TenHave, T. (2007) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2006.09.008 · Cited by 211
Self-citationEstimation and extrapolation of optimal treatment and testing strategies
Robins, J., Orellana, L., & Rotnitzky, A. (2008) · Statistics in Medicine · doi:10.1002/sim.3301 · Cited by 208
Zhou, X. C., Liu, S., Kim, E. S., Herbst, R. S., & Lee, J. J. (2008) · Clinical Trials · doi:10.1177/1740774508091815 · Cited by 206
Q-learning: A data analysis method for constructing adaptive interventions.
Nahum-Shani, I., Qian, M., Almirall, D., Pelham, W. E., Gnagy, B., Fabiano, G. A., Waxmonsky, J. G., Yu, J., & Murphy, S. A. (2012) · Psychological Methods · doi:10.1037/a0029373 · Cited by 174
Self-citationPelham, W. E., Evans, S. W., Gnagy, E. M., & Greenslade, K. E. (1992) · School Psychology Review · doi:10.1080/02796015.1992.12085615 · Cited by 155
Lunceford, J. K., Davidian, M., & Tsiatis, A. A. (2002) · Biometrics · doi:10.1111/j.0006-341x.2002.00048.x · Cited by 145
Adaptive Designs: Terminology and Classification
Dragalin, V. (2006) · Drug Information Journal · doi:10.1177/216847900604000408 · Cited by 142
Flexible treatment strategies in chronic disease: clinical and research implications
Lavori, P. W., Dawson, R., & Rush, A. J. (2000) · Biological Psychiatry · doi:10.1016/s0006-3223(00)00946-x · Cited by 138
Weisz, J. R., Chu, B. C., & Polo, A. J. (2004) · Clinical Psychology Science and Practice · doi:10.1093/clipsy.bph085 · Cited by 137
Outcome predictors in substance use disorders
Ciraulo, D. A., Piechniczek‐Buczek, J., & Iscan, E. N. (2003) · Psychiatric Clinics of North America · doi:10.1016/s0193-953x(02)00106-5 · Cited by 121
Fabiano, G. A., Chacko, A., Pelham, W. E., Robb, J., Walker, K. S., Wymbs, F., Sastry, A. L., Flammer, L., Keenan, J. K., Visweswaraiah, H., et al. (2009) · Behavior Therapy · doi:10.1016/j.beth.2008.05.002 · Cited by 120
Selecting Therapeutic Strategies Based on Efficacy and Death in Multicourse Clinical Trials
Thall, P. F., Sung, H., & Estey, E. H. (2002) · Journal of the American Statistical Association · doi:10.1198/016214502753479202 · Cited by 117
Wahed, A. S., & Tsiatis, A. A. (2004) · Biometrics · doi:10.1111/j.0006-341x.2004.00160.x · Cited by 103
The generalized anxiety spectrum: prevalence, onset, course and outcome
Angst, J., Gamma, A., Baldwin, D. S., Ajdacic‐Gross, V., & Wulf Rössler, A. (2008) · European Archives of Psychiatry and Clinical Neuroscience · doi:10.1007/s00406-008-0832-9 · Cited by 101
Customizing treatment to the patient: Adaptive treatment strategies
Murphy, S. A., Collins, L. M., & Rush, A. J. (2007) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2007.02.001 · Cited by 94
Self-citationRobins, J. M. (1987) · Computers & Mathematics with Applications · doi:10.1016/0898-1221(87)90237-9 · Cited by 91
Pettinati, H. M., Weiss, R. D., Dundon, W. D., Miller, W. R., Donovan, D. M., Ernst, D., & Rounsaville, B. J. (2005) · Journal of Studies on Alcohol Supplement · doi:10.15288/jsas.2005.s15.170 · Cited by 84
McKay, J. R., Horn, D. H. A. V., Oslin, D. W., Lynch, K. G., Ivey, M. A., Ward, K., Drapkin, M. L., Kraut-Becher, J. R., & Coviello, D. M. (2010) · Journal of Consulting and Clinical Psychology · doi:10.1037/a0020700 · Cited by 83
Self-citationLord, C. (2000) · Journal of Autism and Developmental Disorders · doi:10.1023/a:1005591205002 · Cited by 76
Thall, P. F., Wooten, L. H., Logothetis, C. J., Millikan, R. E., & Tannir, N. M. (2007) · Statistics in Medicine · doi:10.1002/sim.2894 · Cited by 75
Covariate-adjusted adaptive randomization in a sarcoma trial with multi-stage treatments
Thall, P. F., & Wathen, J. K. (2005) · Statistics in Medicine · doi:10.1002/sim.2077 · Cited by 74
Wahed, A. S., & Tsiatis, A. A. (2006) · Biometrika · doi:10.1093/biomet/93.1.163 · Cited by 73
Thall, P. F., Logothetis, C., Pagliaro, L. C., Wen, S., Brown, M. A., Williams, D., & Millikan, R. E. (2007) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/djm189 · Cited by 67 · cited 1×
“…trial of treatments for schizophrenia (Stroup et al. 2003), Phase II trials at University of Texas MD Anderson Cancer Center for treating cancer (Thall et al. 2007a), the ExTENd trial of treatments for alcohol dependence by Oslin (2005) at the University of Pennsylvania, and a SMART study of…”
MethodGELLER, D. A., McCarthy, K., Mancuso, E., Gendron, C., & GELLER, D. A. (2009) · Neuropsychiatric Disease and Treatment · doi:10.2147/ndt.s3896 · Cited by 61
Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE): Alzheimer's Disease Trial
Schneider, L. S. S., Ismail, M. S., Dagerman, K., Davis, S. M., Olin, J. T., McManus, D., Pfeiffer, E., Ryan, J. M., Sultzer, D. L., & Tariot, P. N. (2003) · Schizophrenia Bulletin · doi:10.1093/oxfordjournals.schbul.a006991 · Cited by 58
Wigal, S. B., Wigal, T. L., Schuck, S. E. B., Brams, M. N., Williamson, D., Armstrong, R. B., & Starr, H. L. (2011) · Journal of Child and Adolescent Psychopharmacology · doi:10.1089/cap.2010.0047 · Cited by 57
Jones, H. E., Wong, C. J., Tuten, M., & Stitzer, M. L. (2005) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2005.01.006 · Cited by 56
Brown, R. T. (2008) · Choice Reviews Online · doi:10.5860/choice.45-4410 · Cited by 56
Shiozawa, T., Nikaido, T., 清水, 元., Zhai, Y., & Fujii, S. (1997) · Cancer · doi:10.1002/(sici)1097-0142(19971215)80:12 · Cited by 54
Orellana, L., Rotnitzky, A., & Robins, J. M. (2010) · The International Journal of Biostatistics · doi:10.2202/1557-4679.1242 · Cited by 53
Examining clinical judgment in an adaptive intervention design: The fast track program.
Bierman, K. L., Nix, R. L., Maples, J. J., & Murphy, S. A. (2006) · Journal of Consulting and Clinical Psychology · doi:10.1037/0022-006x.74.3.468 · Cited by 51
Self-citationOrigins, issues and options in the development of the combined behavioral intervention.
Longabaugh, R., Zweben, A., LoCastro, J. S., & Miller, W. R. (2005) · Journal of Studies on Alcohol Supplement · doi:10.15288/jsas.2005.s15.179 · Cited by 49
Jones, H. E., O’Grady, K. E., & Tuten, M. (2011) · American Journal on Addictions · doi:10.1111/j.1521-0391.2011.00119.x · Cited by 47
Liu‐Seifert, H., Osuntokun, O. O., & Feldman, P. D. (2011) · Comprehensive Psychiatry · doi:10.1016/j.comppsych.2010.12.003 · Cited by 46
Efficient design and inference for multistage randomized trials of individualized treatment policies
Dawson, R., & Lavori, P. W. (2011) · Biostatistics · doi:10.1093/biostatistics/kxr016 · Cited by 44
Adaptive Interventions in Drug Court
Marlowe, D. B., Festinger, D. S., Arabia, P. L., Dugosh, K. L., Benasutti, K. M., Croft, J. R., & McKay, J. R. (2008) · Criminal Justice Review · doi:10.1177/0734016808320325 · Cited by 33
Weisz, J. R. (2004) · Clinical Psychology Science and Practice · doi:10.1093/clipsy/bph085 · Cited by 32
Joss, R., Alberto, P., Bleher, E. A., Ludwig, C., Siegenthaler, P. A., Martinelli, G., Sauter, C., Schatzmann, E., & Senn, H.-J. (1994) · Annals of Oncology · doi:10.1093/oxfordjournals.annonc.a058731 · Cited by 24
Stulz, N., Gallop, R., Lutz, W., Wrenn, G., & Crits-Christoph, P. (2009) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2009.08.009 · Cited by 19
Implementation of an adaptive group sequential design in a bioequivalence study
Bandyopadhyay, N., & Dragalin, V. (2007) · Pharmaceutical Statistics · doi:10.1002/pst.252 · Cited by 18
Honigmann, P., Fischer, H., Kurmann, A. A., Audigé, L., Schüpfer, G., & Metzger, J. (2007) · BMC Surgery · doi:10.1186/1471-2482-7-22 · Cited by 16
Q-Learning: A data analysis method for constructing adaptive interventions
Nahum-Shani, I. B., Qian, M. X., Pelham, W. E., Gnagy, B., Fabiano, G. A., Waxmonsky, J. G., Yu, J., & Murphy, S. A. (2010) · Cited by 3
Self-citation
Research works printed but not linked: 11
- Cafiero J, 2005, Meaningful Exchanges for People with Autism: An Introduction to Augmentative and Alternative Communication
- Hammerness P, 2009, Neuropsychiatr. Dis. Treat., 5, 215
- Jones H, 2010, Reinforcement-Based Treatment for Pregnant Drug Abusers (HOME II)
- Kasari C, 2009, Developmental and Augmented Intervention for Facilitating Expressive Language (CCNIA)
- Miller WR, 2003, Alcohol Clin. Exp. Res., 27, 113
- Orellana L, 2010, Int. J. Biostat., 6
- Oslin D, 2005, Managing Alcoholism in People Who Do Not Respond to Naltrexone (EXTEND)
- Pettinati HM, 2004, Medical Management Treatment Manual COMBINE Monograph Series, Volume 2,
- Robins JM, 1986, Comput. Math. Appl., 14, 1393
- SAS Inst., 2008, SAS/STAT 9.2 User's Guide.
- Tannir NM, 2010, Sequential Two-Agent Assessment in Renal Cell Carcinoma Therapy
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Evaluating Digital Health Interventions
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Skivington, K., Matthews, L., Simpson, S. A., Craig, P., Baird, J., Blazeby, J. M., Boyd, K., Craig, N. J., French, D., McIntosh, E., et al. (2021) · Health Technology Assessment · doi:10.3310/hta25570 · Cited by 585
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Metadata
- Authors
- Lei, H., Nahum-Shani, I., Lynch, K., Oslin, D., & Murphy, S. A.
- Affiliations
- University of Michigan (US)
- University of Pennsylvania (US)
- Philadelphia VA Medical Center (US)
- Venue
- Annual Review of Clinical Psychology
- Publisher
- Annual Reviews
- Published
- 2012-04-27
- Volume
- 8
- Issue
- 1
- Pages
- 21-48
- ISSN
- 1548-5943 (ISSN-L)
- 1548-5951
- PMC
- PMC3887122
- OpenAlex
- W2163084572
- Cited by
- 557
- References
- 78
- Citations by year
- 2026: 24 · 2025: 32 · 2024: 63 · 2023: 37 · 2022: 46 · 2021: 56 · 2020: 50 · 2019: 55 · 2018: 47 · 2017: 33 · 2016: 34 · 2015: 25 · 2014: 35 · 2013: 14 · 2012: 4
- FWCI
- 3.73
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Locations
- Annual Review of Clinical Psychology (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (5r01aa014851-04)
- National Institute on Alcohol Abuse and Alcoholism (R01 AA-014851, RC1AA019092)
- National Institute of Mental Health (R01MH080015)
- National Institute on Drug Abuse (P50DA010075)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Keywords
- adaptive interventions, sequential multiple assignment randomized trial, treatment response, medication adherence, naltrexone, experimental design comparison
- MeSH terms
- Mental Disorders, Humans, Research Design, United States, Program Evaluation, Randomized Controlled Trials as Topic, Program Development, Patient-Centered Care
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