Statistical Analysis With Missing Data

Modeling the Drop-Out Mechanism in Repeated-Measures Studies

Little, R. J. A. (1995) · Journal of the American Statistical Association · doi:10.1080/01621459.1995.10476615 · Cited by 1,522

Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): Explanation and elaboration

Vandenbroucke, J. P., von Elm, E., Altman, D. G., Gøtzsche, P. C., Mulrow, C. D., Pocock, S. J., Poole, C., Schlesselman, J. J., & Egger, M. (2014) · International Journal of Surgery · doi:10.1016/j.ijsu.2014.07.014 · Cited by 2,969

Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): Explanation and Elaboration

Vandenbroucke, J. P., von Elm, E., Altman, D. G., Gøtzsche, P. C., Mulrow, C. D., Pocock, S. J., Poole, C., Schlesselman, J. J., & Egger, M. (2007) · Epidemiology · doi:10.1097/ede.0b013e3181577511 · Cited by 2,779

Increasing value and reducing waste in research design, conduct, and analysis

Ioannidis, J. P. A., Greenland, S., Hlatky, M. A., Khoury, M. J., Macleod, M. R., Moher, D., Schulz, K. F., & Tibshirani, R. (2014) · The Lancet · doi:10.1016/s0140-6736(13)62227-8 · Cited by 1,597

The Society of Thoracic Surgeons 2008 Cardiac Surgery Risk Models: Part 2—Isolated Valve Surgery

O'Brien, S. M., Shahian, D. M., Filardo, G., Ferraris, V. A., Haan, C. K., Rich, J. B., Normand, S.-L. T., DeLong, E. R., Shewan, C. M., Dokholyan, R. S., et al. (2009) · The Annals of Thoracic Surgery · doi:10.1016/j.athoracsur.2009.05.056 · Cited by 1,259

The Society of Thoracic Surgeons 2008 Cardiac Surgery Risk Models: Part 1—Coronary Artery Bypass Grafting Surgery

Shahian, D. M., O'Brien, S. M., Filardo, G., Ferraris, V. A., Haan, C. K., Rich, J. B., Normand, S.-L. T., DeLong, E. R., Shewan, C. M., Dokholyan, R. S., et al. (2009) · The Annals of Thoracic Surgery · doi:10.1016/j.athoracsur.2009.05.053 · Cited by 1,256

Inverse probability weighted estimation for general missing data problems

Wooldridge, J. M. (2007) · Journal of Econometrics · doi:10.1016/j.jeconom.2007.02.002 · Cited by 1,029

Missing Data in Clinical Research: A Tutorial on Multiple Imputation

Austin, P. C., White, I. R., Lee, D. S., & van Buuren, S. (2021) · Canadian Journal of Cardiology · doi:10.1016/j.cjca.2020.11.010 · Cited by 1,006

zCompositions — R package for multivariate imputation of left-censored data under a compositional approach

Palarea-Albaladejo, J., & Martín-Fernández, J. A. (2015) · Chemometrics and Intelligent Laboratory Systems · doi:10.1016/j.chemolab.2015.02.019 · Cited by 965

Effects of missing data in social networks

Kossinets, G. (2006) · Social Networks · doi:10.1016/j.socnet.2005.07.002 · Cited by 926

Fetal antiepileptic drug exposure and cognitive outcomes at age 6 years (NEAD study): a prospective observational study

Meador, K. J., Baker, G. A., Browning, N., Cohen, M. J., Bromley, R. L., Clayton-Smith, J., Kalayjian, L. A., Kanner, A., Liporace, J. D., Pennell, P. B., et al. (2013) · The Lancet Neurology · doi:10.1016/s1474-4422(12)70323-x · Cited by 834

Risk of hepatocellular cancer in patients with non-alcoholic fatty liver disease

Kanwal, F., Kramer, J. R., Mapakshi, S., Natarajan, Y., Chayanupatkul, M., Richardson, P. A., Li, L., Desiderio, R., Thrift, A. P., Asch, S. M., et al. (2018) · Gastroenterology · doi:10.1053/j.gastro.2018.08.024 · Cited by 795

School-based suicide prevention programmes: the SEYLE cluster-randomised, controlled trial

Wasserman, D., Hoven, C. W., Wasserman, C., Wall, M., Eisenberg, R., Hadlaczky, G., Kelleher, I., Sarchiapone, M., Apter, A., Balazs, J., et al. (2015) · The Lancet · doi:10.1016/s0140-6736(14)61213-7 · Cited by 781

The GRoLTS-Checklist: Guidelines for Reporting on Latent Trajectory Studies

van de Schoot, R., Sijbrandij, M., Winter, S. D., Depaoli, S., & Vermunt, J. K. (2017) · Structural Equation Modeling: A Multidisciplinary Journal · doi:10.1080/10705511.2016.1247646 · Cited by 721

Predictive Analytics in Information Systems Research

Shmueli, G., & Koppius, O. (2010) · doi:10.2139/ssrn.1606674 · Cited by 676

A Review of Domain Adaptation without Target Labels

Kouw, W. M., & Loog, M. (2021) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2019.2945942 · Cited by 613

Multiple imputation of missing values was not necessary before performing a longitudinal mixed-model analysis

Twisk, J., de Boer, M., de Vente, W., & Heymans, M. (2013) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2013.03.017 · Cited by 568

Clinical validity of PROMIS depression, anxiety, and anger across diverse clinical samples

Schalet, B. D., Pilkonis, P. A., Yu, L., Dodds, N., Johnston, K. L., Yount, S., Riley, W., & Cella, D. (2016) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2015.08.036 · Cited by 507

Trends in Smoking Among Adults With Mental Illness and Association Between Mental Health Treatment and Smoking Cessation

Cook, B. L., Wayne, G. F., Kafali, E. N., Liu, Z., Shu, C., & Flores, M. (2014) · JAMA · doi:10.1001/jama.2013.284985 · Cited by 519

Comparison of performance of data imputation methods for numeric dataset

Jadhav, A., Pramod, D., & Ramanathan, K. (2019) · Applied Artificial Intelligence · doi:10.1080/08839514.2019.1637138 · Cited by 471

The Accuracy of Self-Reported Internet Use—A Validation Study Using Client Log Data

Scharkow, M. (2016) · Communication Methods and Measures · doi:10.1080/19312458.2015.1118446 · Cited by 408

A review of solutions for diagnostic accuracy studies with an imperfect or missing reference standard

Reitsma, J. B., Rutjes, A. W. S., Khan, K. S., Coomarasamy, A., & Bossuyt, P. M. (2009) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2009.02.005 · Cited by 405

PCSK9 genetic variants and risk of type 2 diabetes: a mendelian randomisation study

Schmidt, A. F., Swerdlow, D. I., Holmes, M. V., Patel, R. S., Fairhurst-Hunter, Z., Lyall, D. M., Hartwig, F. P., Horta, B. L., Hyppönen, E., Power, C., et al. (2017) · The Lancet Diabetes & Endocrinology · doi:10.1016/s2213-8587(16)30396-5 · Cited by 380

The Effects of Data Quality on Machine Learning Performance on Tabular Data

Mohammed, S., Budach, L., Feuerpfeil, M., Ihde, N., Nathansen, A., Noack, N., Patzlaff, H., Naumann, F., & Harmouch, H. (2025) · Information Systems · doi:10.1016/j.is.2025.102549 · Cited by 331

Career success: The role of teenage career aspirations, ambition value and gender in predicting adult social status and earnings

Ashby, J. S., & Schoon, I. (2010) · Journal of Vocational Behavior · doi:10.1016/j.jvb.2010.06.006 · Cited by 312

Attrition in randomized controlled clinical trials: methodological issues in psychopharmacology

Leon, A. C., Mallinckrodt, C. H., Chuang-Stein, C., Archibald, D. G., Archer, G. E., & Chartier, K. (2006) · Biological Psychiatry · doi:10.1016/j.biopsych.2005.10.020 · Cited by 303

Enhancing vigilance in operators with prefrontal cortex transcranial direct current stimulation (tDCS)

Nelson, J. T., McKinley, R. A., Golob, E. J., Warm, J. S., & Parasuraman, R. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2012.11.061 · Cited by 300

Effects of cognitive behaviour therapy for worry on persecutory delusions in patients with psychosis (WIT): a parallel, single-blind, randomised controlled trial with a mediation analysis.

Freeman, D., Dunn, G., Startup, H., Pugh, K., Cordwell, J., Mander, H., Černis, E., Wingham, G., Shirvell, K., & Kingdon, D. (2015) · The Lancet Psychiatry · doi:10.1016/s2215-0366(15)00039-5 · Cited by 295

Purpose in life and reduced incidence of stroke in older adults: 'The Health and Retirement Study'

Kim, E. S., Sun, J. K., Park, N., & Peterson, C. (2013) · Journal of Psychosomatic Research · doi:10.1016/j.jpsychores.2013.01.013 · Cited by 274

Adolescent Eating Disorders Predict Psychiatric, High-Risk Behaviors and Weight Outcomes in Young Adulthood

Micali, N., Solmi, F., Horton, N. J., Crosby, R. D., Eddy, K. T., Calzo, J. P., Sonneville, K. R., Swanson, S. A., & Field, A. E. (2015) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1016/j.jaac.2015.05.009 · Cited by 248

Effectiveness of Internet-based cognitive behaviour therapy for depression in routine psychiatric care

Hedman, E., Ljótsson, B., Kaldo, V., Hesser, H., El Alaoui, S., Kraepelien, M., Andersson, E., Rück, C., Svanborg, C., Andersson, G., et al. (2014) · Journal of Affective Disorders · doi:10.1016/j.jad.2013.10.023 · Cited by 224

Child effortful control, teacher–student relationships, and achievement in academically at-risk children: Additive and interactive effects

Liew, J., Chen, Q., & Hughes, J. N. (2010) · Early Childhood Research Quarterly · doi:10.1016/j.ecresq.2009.07.005 · Cited by 241

Anxiety sensitivity and interoceptive exposure: A transdiagnostic construct and change strategy

Boswell, J. F., Farchione, T. J., Sauer-Zavala, S., Murray, H. W., Fortune, M. R., & Barlow, D. H. (2013) · Behavior Therapy · doi:10.1016/j.beth.2013.03.006 · Cited by 232

Techniques for Handling Missing Data in Secondary Analyses of Large Surveys

Langkamp, D. L., Lehman, A., & Lemeshow, S. (2010) · Academic Pediatrics · doi:10.1016/j.acap.2010.01.005 · Cited by 218

Evidence from diverse clinical populations supported clinical validity of PROMIS pain interference and pain behavior

Askew, R. L., Cook, K. F., Revicki, D. A., Cella, D., & Amtmann, D. (2016) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2015.08.035 · Cited by 212

Randomised controlled non-inferiority trial with 3-year follow-up of internet-delivered versus face-to-face group cognitive behavioural therapy for depression

Andersson, G., Hesser, H., Veilord, A., Svedling, L., Andersson, F., Sleman, O., Mauritzson, L., Sarkohi, A., Claesson, E., Zetterqvist, V., et al. (2013) · Journal of Affective Disorders · doi:10.1016/j.jad.2013.08.022 · Cited by 195

Test use and assessment practices of school psychologists in the United States: Findings from the 2017 National Survey

Benson, N. F., Floyd, R. G., Kranzler, J. H., Eckert, T. L., Fefer, S. A., & Morgan, G. B. (2019) · Journal of School Psychology · doi:10.1016/j.jsp.2018.12.004 · Cited by 202

Transforming wealth: Using the inverse hyperbolic sine (IHS) and splines to predict youth’s math achievement

Friedline, T., Masa, R. D., & Chowa, G. A. N. (2015) · Social Science Research · doi:10.1016/j.ssresearch.2014.08.018 · Cited by 201

Modeling individual differences in randomized experiments using growth models: recommendations for design, statistical analysis and reporting of results of internet interventions

Hesser, H. (2015) · Internet Interventions · doi:10.1016/j.invent.2015.02.003 · Cited by 192

Breastfeeding as an exposure pathway for perfluorinated alkylates

Mogensen, U. B., Grandjean, P., Nielsen, F., Weihe, P., & Budtz-Jørgensen, E. (2015) · Environmental Science & Technology · doi:10.1021/acs.est.5b02237 · Cited by 190

Long-term impacts of the CARE program on teachers' self-reported social and emotional competence and well-being

Jennings, P. A., Doyle, S., Oh, Y., Rasheed, D., Frank, J. L., & Brown, J. L. (2019) · Journal of School Psychology · doi:10.1016/j.jsp.2019.07.009 · Cited by 186

Fear of missing out and problematic social media use as mediators between emotional support from social media and phubbing behavior

Fang, J., Wang, X., Wen, Z., & Zhou, J. (2020) · Addictive Behaviors · doi:10.1016/j.addbeh.2020.106430 · Cited by 186

Injection fears and COVID-19 vaccine hesitancy

Freeman, D., Lambe, S., Yu, L.-M., Freeman, J., Chadwick, A., Vaccari, C., Waite, F., Rosebrock, L., Petit, A., Vanderslott, S., et al. (2023) · Psychological Medicine · doi:10.1017/s0033291721002609 · Cited by 175

Multiple imputation of missing repeated outcome measurements did not add to linear mixed-effects models

Peters, S. A. E., Bots, M. L., den Ruijter, H. M., Palmer, M. K., Grobbee, D. E., Crouse, J. R., O’Leary, D. H., Evans, G. W., Raichlen, J. S., Moons, K. G. M., et al. (2012) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2011.11.012 · Cited by 165

24- and 36-Week Outcomes for the Child/Adolescent Anxiety Multimodal Study (CAMS)

Piacentini, J., Bennett, S., Compton, S. N., Kendall, P. C., Birmaher, B., Albano, A. M., March, J., Sherrill, J., Sakolsky, D., Ginsburg, G., et al. (2014) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1016/j.jaac.2013.11.010 · Cited by 164

Child neglect, psychological abuse and smartphone addiction among Chinese adolescents: The roles of emotional intelligence and coping style

Sun, J., Liu, Q., & Yu, S. (2019) · Computers in Human Behavior · doi:10.1016/j.chb.2018.08.032 · Cited by 161

Intelligent system for lighting control in smart cities

De Paz, J. F., Bajo, J., Rodríguez, S., Villarrubia, G., & Corchado, J. M. (2016) · Information Sciences · doi:10.1016/j.ins.2016.08.045 · Cited by 146

Resistance in repressive contexts: A comprehensive test of psychological predictors.

Ayanian, A. H., Tausch, N., Acar, Y. G., Chayinska, M., Cheung, W.-Y., & Lukyanova, Y. (2021) · Journal of Personality and Social Psychology · doi:10.1037/pspi0000285 · Cited by 137

A prospective study of familial conflict, psychological stress, and the development of substance use disorders in adolescence

Skeer, M., McCormick, M. C., Normand, S.-L. T., Buka, S. L., & Gilman, S. E. (2009) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2009.03.017 · Cited by 135

Ideal free settlement of California’s Northern Channel Islands

Winterhalder, B., Kennett, D. J., Grote, M. N., & Bartruff, J. (2010) · Journal of Anthropological Archaeology · doi:10.1016/j.jaa.2010.07.001 · Cited by 125

Will materialism lead to happiness? A longitudinal analysis of the mediating role of psychological needs satisfaction

Wang, R., Liu, H., Jiang, J., & Song, Y. (2017) · Personality and Individual Differences · doi:10.1016/j.paid.2016.10.014 · Cited by 111

Functional connectivity changes associated with fMRI neurofeedback of right inferior frontal cortex in adolescents with ADHD

Rubia, K., Criaud, M., Wulff, M., Alegria, A., Brinson, H., Barker, G., Stahl, D., & Giampietro, V. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2018.11.055 · Cited by 111

Self-medication and health insurance coverage in Mexico

Pagán, J. A., Ross, S., Yau, J., & Polsky, D. (2006) · Health Policy · doi:10.1016/j.healthpol.2005.03.007 · Cited by 111

Stress and health behaviour over the life course

Umberson, D., Liu, H., & Reczek, C. (2008) · Advances in Life Course Research · doi:10.1016/s1040-2608(08)00002-6 · Cited by 99

The exacerbating role of perceived social support and the “buffering” role of depression in the relation between sensation seeking and adolescent smartphone addiction

Wang, P., Lei, L., Wang, X., Nie, J., Chu, X., & Jin, S. (2018) · Personality and Individual Differences · doi:10.1016/j.paid.2018.04.009 · Cited by 98

Transforming cerebrospinal fluid Aβ42 measures into calculated Pittsburgh compound B units of brain Aβ amyloid

Weigand, S. D., Vemuri, P., Wiste, H. J., Senjem, M. L., Pankratz, V. S., Aisen, P. S., Weiner, M. W., Petersen, R. C., Shaw, L. M., Trojanowski, J. Q., et al. (2011) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2010.08.230 · Cited by 93

Inflammation and oxidant-stress in -thalassemia patients treated with iron chelators deferasirox (ICL670) or deferoxamine: an ancillary study of the Novartis CICL670A0107 trial

Walter, P. B., Macklin, E. A., Porter, J., Evans, P., Kwiatkowski, J. L., Neufeld, E. J., Coates, T., Giardina, P. J., Vichinsky, E., Olivieri, N., et al. (2008) · Haematologica · doi:10.3324/haematol.11755 · Cited by 87

External Validation of Diagnostic Models to Estimate the Risk of Malignancy in Adnexal Masses

Van Holsbeke, C., Van Calster, B., Bourne, T., Ajossa, S., Testa, A. C., Guerriero, S., Fruscio, R., Lissoni, A. A., Czekierdowski, A., Savelli, L., et al. (2012) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-11-0879 · Cited by 87

Determinants of pain treatment response and nonresponse: identification of TMD patient subgroups

Litt, M. D., & Porto, F. B. (2013) · The Journal of Pain · doi:10.1016/j.jpain.2013.07.017 · Cited by 86

Bibliometric evaluation vs. informed peer review: Evidence from Italy

Bertocchi, G., Gambardella, A., Jappelli, T., Nappi, C. A., & Peracchi, F. (2015) · Research Policy · doi:10.1016/j.respol.2014.08.004 · Cited by 86

Effect of Continuing Olanzapine vs Placebo on Relapse Among Patients With Psychotic Depression in Remission: The STOP-PD II Randomized Clinical Trial

Flint, A. J., Meyers, B. S., Rothschild, A. J., Whyte, E. M., Alexopoulos, G. S., Rudorfer, M. V., Marino, P., Banerjee, S., Pollari, C. D., Wu, Y., et al. (2019) · JAMA · doi:10.1001/jama.2019.10517 · Cited by 85

Psychological aspects of eating behavior as predictors of 10-y weight changes after surgical and conventional treatment of severe obesity: results from the Swedish Obese Subjects intervention study

Konttinen, H., Peltonen, M., Sjöström, L., Carlsson, L., & Karlsson, J. (2015) · The American Journal of Clinical Nutrition · doi:10.3945/ajcn.114.095182 · Cited by 83

Preventing Youth Violence and Dropout: A Randomized Field Experiment

Heller, S., Pollack, H., Ander, R., & Ludwig, J. (2013) · doi:10.3386/w19014 · Cited by 79

Investigating how college students’ task definitions and plans relate to self-regulated learning processing and understanding of a complex science topic

Greene, J. A., Hutchison, L. A., Costa, L.-J., & Crompton, H. (2012) · Contemporary Educational Psychology · doi:10.1016/j.cedpsych.2012.02.002 · Cited by 74

Cognitive therapy for internalised stigma in people experiencing psychosis: a pilot randomised controlled trial

Morrison, A. P., Burke, E., Murphy, E., Pyle, M., Bowe, S., Varese, F., Dunn, G., Chapman, N., Hutton, P., Welford, M., et al. (2016) · Psychiatry Research · doi:10.1016/j.psychres.2016.04.024 · Cited by 72

Combining physical and cognitive training to improve kindergarten children’s executive functions: A cluster randomized controlled trial

Schmidt, M., Mavilidi, M. F., Singh, A., & Englert, C. (2020) · Contemporary Educational Psychology · doi:10.1016/j.cedpsych.2020.101908 · Cited by 70

Estimating treatment effects from longitudinal clinical trial data with missing values: comparative analyses using different methods

Houck, P. R., Mazumdar, S., Koru-Sengul, T., Tang, G., Mulsant, B. H., Pollock, B. G., & Reynolds, C. F. (2004) · Psychiatry Research · doi:10.1016/j.psychres.2004.08.001 · Cited by 65

Imputing Phenotypes for Genome-wide Association Studies

Hormozdiari, F., Kang, E. Y., Bilow, M., Ben-David, E., Vulpe, C., McLachlan, S., Lusis, A. J., Han, B., & Eskin, E. (2016) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2016.04.013 · Cited by 53

Missing the missing values: The ugly duckling of fairness in machine learning

Fernando, M., Cèsar, F., David, N., & José, H. (2021) · International Journal of Intelligent Systems · doi:10.1002/int.22415 · Cited by 62

Associations between childhood maltreatment latent classes and eating disorder symptoms in a nationally representative sample of young adults in the United States

Hazzard, V. M., Bauer, K. W., Mukherjee, B., Miller, A. L., & Sonneville, K. R. (2019) · Child Abuse & Neglect · doi:10.1016/j.chiabu.2019.104171 · Cited by 59

A Depression Prevention Intervention for Adolescents in the Emergency Department

Ranney, M. L., Freeman, J. R., Connell, G., Spirito, A., Boyer, E., Walton, M., Guthrie, K. M., & Cunningham, R. M. (2016) · Journal of Adolescent Health · doi:10.1016/j.jadohealth.2016.04.008 · Cited by 53

Preoperative multimodal prehabilitation before elective colorectal cancer surgery in patients with WHO performance status I or II: randomized clinical trial

Bojesen, R. D., Dalton, S. O., Skou, S. T., Jørgensen, L. B., Walker, L. R., Eriksen, J. R., Grube, C., Justesen, T. F., Johansen, C., Slooter, G., et al. (2023) · BJS Open · doi:10.1093/bjsopen/zrad134 · Cited by 53

Effects of combination lipid therapy on coronary stenosis progression and clinical cardiovascular events in coronary disease patients with metabolic syndrome: a combined analysis of the Familial Atherosclerosis treatment study (FATS), the HDL-Atherosclerosis treatment study (HATS) and the Armed Forces regression Study (AFREGS)

Zhao, X.-Q., Krasuski, R. A., Baer, J., Whitney, E. J., Neradilek, B., Chait, A., Marcovina, S., Albers, J. J., & Brown, B. G. (2009) · The American Journal of Cardiology · doi:10.1016/j.amjcard.2009.07.035 · Cited by 48

Beyond the heritability of life satisfaction – The roles of personality and twin-specific influences

Hahn, E., Johnson, W., & Spinath, F. M. (2013) · Journal of Research in Personality · doi:10.1016/j.jrp.2013.07.003 · Cited by 48

A systematic review finds variable use of the intention-to-treat principle in musculoskeletal randomized controlled trials with missing data

Joseph, R., Sim, J., Ogollah, R., & Lewis, M. (2015) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2014.09.002 · Cited by 50

Two-way imputation: a Bayesian method for estimating missing scores in tests and questionnaires, and an accurate approximation

Van Ginkel, J. R., Andries Van der Ark, L., Sijtsma, K., & Vermunt, J. K. (2007) · Computational Statistics & Data Analysis · doi:10.1016/j.csda.2006.12.022 · Cited by 46

The interpersonal character of teacher expectations: The perceived teacher-student relationship as an antecedent of teachers' track recommendations

Timmermans, A. C., van der Werf, M. P. C. G., & Rubie-Davies, C. M. (2019) · Journal of School Psychology · doi:10.1016/j.jsp.2019.02.004 · Cited by 45

Changes of valued behaviors and functioning during an Acceptance and Commitment Therapy Intervention

Wersebe, H., Lieb, R., Meyer, A. H., Hoyer, J., Wittchen, H.-U., & Gloster, A. T. (2017) · Journal of Contextual Behavioral Science · doi:10.1016/j.jcbs.2016.11.005 · Cited by 43

The impact of structured blood glucose testing on attitudes toward self-management among poorly controlled, insulin-naïve patients with type 2 diabetes

Fisher, L., Polonsky, W. H., Parkin, C. G., Jelsovsky, Z., Petersen, B., & Wagner, R. S. (2012) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2011.12.016 · Cited by 44

Dysphoria and anhedonia as risk factors for disability or death in older persons: implications for the assessment of geriatric depression

Covinsky, K. E., Cenzer, I. S., Yaffe, K., O'Brien, S., & Blazer, D. G. (2014) · The American Journal of Geriatric Psychiatry · doi:10.1016/j.jagp.2012.12.001 · Cited by 43

Psychological flexibility is not a single dimension: The distinctive flexibility profiles of underweight, overweight, and obese people

Ciarrochi, J., Sahdra, B., Marshall, S., Parker, P., & Horwath, C. (2014) · Journal of Contextual Behavioral Science · doi:10.1016/j.jcbs.2014.07.002 · Cited by 42

Equivalent harm? The relative roles of maltreatment and exposure to intimate partner violence in antisocial outcomes for young adults

Park, A., Smith, C., & Ireland, T. (2012) · Children and Youth Services Review · doi:10.1016/j.childyouth.2012.01.029 · Cited by 40

"Wellness Champions for Change," a multi-level intervention to improve school-level implementation of local wellness policies: study protocol for a cluster randomized trial

Lane, H. G., Deitch, R., Wang, Y., Black, M. M., Dunton, G. F., Aldoory, L., Turner, L., Parker, E. A., Henley, S. C., Saksvig, B., et al. (2018) · Contemporary Clinical Trials · doi:10.1016/j.cct.2018.10.008 · Cited by 39

Birth weight, early life course BMI, and body size change: chains of risk to adult inflammation?

Goosby, B. J., Cheadle, J. E., & McDade, T. (2016) · Social Science & Medicine · doi:10.1016/j.socscimed.2015.11.040 · Cited by 33

Exposure to interparental intimate partner violence and the development of borderline features in adolescents

Sharp, C., Vanwoerden, S., Jouriles, E. N., Godfrey, D. A., Babcock, J., McLaren, V., McFarlane, J., Brashear, B., Walton, Q., & Temple, J. R. (2020) · Child Abuse & Neglect · doi:10.1016/j.chiabu.2020.104448 · Cited by 34

Approaches to addressing missing values, measurement error, and confounding in epidemiologic studies

van Smeden, M., Penning de Vries, B. B. L., Nab, L., & Groenwold, R. H. H. (2021) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2020.11.006 · Cited by 32

Maternal and paternal depression and child mental health trajectories: evidence from the Avon Longitudinal Study of Parents and Children

Rajyaguru, P., Kwong, A. S. F., Braithwaite, E., & Pearson, R. M. (2021) · BJPsych Open · doi:10.1192/bjo.2021.959 · Cited by 31

The HCUP SID imputation project: improving statistical inferences for health disparities research by imputing missing race data

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