The DOI matches its Crossref record.
Models for Longitudinal Data: A Generalized Estimating Equation Approach
Abstract
This article discusses extensions of generalized linear models for the analysis of longitudinal data. Two approaches are considered: subject-specific (SS) models in which heterogeneity in regression parameters is explicitly modelled; and population-averaged (PA) models in which the aggregate response for the population is the focus. We use a generalized estimating equation approach to fit both classes of models for discrete and continuous outcomes. When the subject-specific parameters are assumed to follow a Gaussian distribution, simple relationships between the PA and SS parameters are available. The methods are illustrated with an analysis of data on mother's smoking and children's respiratory disease.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Items 101–156 of 156
Sherman, M., & Cessie, S. L. (1997) · Communications in Statistics - Simulation and Computation · doi:10.1080/03610919708813417 · Cited by 103
Age-dependent and gender-specific changes in mouse tissue iron by strain
Hahn, P., Song, Y., Ying, G.-S., He, X., Beard, J., & Dunaief, J. L. (2009) · Experimental Gerontology · doi:10.1016/j.exger.2009.06.006 · Cited by 98
“Thus, in the comparison of iron levels in retina and RPE/choroid, we used the generalized estimating equation (GEE) approach to adjust for the correlation between paired eyes of the same mouse (Zeger et al., 1988).”
MethodCohen, D. M., Patel, C. B., Ahobila‐Vajjula, P., Sundberg, L. M., Chacko, T., Liu, S., & Narayana, P. A. (2009) · NMR in Biomedicine · doi:10.1002/nbm.1343 · Cited by 96
Eisenberg, M. (2001) · Archives of Sexual Behavior · doi:10.1023/a:1011958816438 · Cited by 94
Association of fish oil supplement use with preservation of brain volume and cognitive function
Daiello, L. A., Gongvatana, A., Dunsiger, S., Cohen, R. A., Ott, B. R., & Initiative, A. D. N. (2015) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2014.02.005 · Cited by 89
Joint analysis of SNP and gene expression data in genetic association studies of complex diseases
Huang, Y.-T., VanderWeele, T. J., & Lin, X. (2014) · The Annals of Applied Statistics · doi:10.1214/13-aoas690 · Cited by 88
Situational Correlates of Abstinence Self-Efficacy.
Gwaltney, C. J., Shiffman, S., & Sayette, M. A. (2005) · Journal of Abnormal Psychology · doi:10.1037/0021-843x.114.4.649 · Cited by 87
Kramer, J.-N., Künzler, F., Mishra, V., Smith, S. N., Kotz, D., Scholz, U., Fleisch, E., & Kowatsch, T. (2020) · Annals of Behavioral Medicine · doi:10.1093/abm/kaaa002 · Cited by 84
Rhenman, A., Berglund, L., Brodin, T., Olovsson, M., Milton, K., Hadziosmanovic, N., & Holte, J. (2015) · Human Reproduction · doi:10.1093/humrep/deu295 · Cited by 79
Wessler, B. S., Nelson, J., Park, J. G., McGinnes, H., Gulati, G., Brazil, R., Van Calster, B., van Klaveren, D., Venema, E., Steyerberg, E., et al. (2021) · Circulation: Cardiovascular Quality and Outcomes · doi:10.1161/circoutcomes.121.007858 · Cited by 83
Relationships between features associated with vomiting in purging-type eating disorders
Reba, L., Thornton, L., Tozzi, F., Klump, K. L., Brandt, H., Crawford, S., Crow, S., Fichter, M. M., Halmi, K. A., Johnson, C., et al. (2005) · International Journal of Eating Disorders · doi:10.1002/eat.20189 · Cited by 77
Merle, B. M. J., Delyfer, M.-N., Korobelnik, J.-F., Rougier, M.-B., Malet, F., Féart, C., Le Goff, M., Peuchant, E., Letenneur, L., Dartigues, J.-F., et al. (2013) · The Journal of Nutrition · doi:10.3945/jn.112.171033 · Cited by 78
Symptoms of distress as prospective predictors of pain-related sciatica treatment outcomes
Edwards, R. R., Klick, B., Buenaver, L., Max, M. B., Haythornthwaite, J. A., Keller, R. B., & Atlas, S. J. (2007) · Pain · doi:10.1016/j.pain.2006.10.026 · Cited by 75
Palacio-Mejía, L. S., Hernández-Ávila, J. E., Hernández-Ávila, M., Dyer-Leal, D., Barranco, A., Quezada-Sánchez, A. D., Alvarez-Aceves, M., Cortés-Alcalá, R., Fernández- Wheatley, J. L., Ordoñez-Hernández, I., et al. (2022) · The Lancet Regional Health - Americas · doi:10.1016/j.lana.2022.100303 · Cited by 77
Attention bias modification for youth with social anxiety disorder
Pergamin‐Hight, L., Pine, D. S., Fox, N. A., & Bar‐Haim, Y. (2016) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.12599 · Cited by 72
Neocortical origin and progression of gray matter atrophy in nonamnestic Alzheimer's disease
Phillips, J. S., Da Re, F., Dratch, L., Xie, S. X., Irwin, D. J., McMillan, C. T., Vaishnavi, S. N., Ferrarese, C., Lee, E. B., Shaw, L. M., et al. (2018) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2017.11.008 · Cited by 74
Brown, C. H., Kellam, S. G., Kaupert, S., Muthén, B. O., Wang, W., Muthén, L. K., Chamberlain, P., PoVey, C. L., Cady, R., Valente, T. W., et al. (2012) · Administration and Policy in Mental Health and Mental Health Services Research · doi:10.1007/s10488-011-0387-3 · Cited by 68
Beckham, J. C., Feldman, M. E., Vrana, S. R., Mozley, S. L., Erkanli, A., Clancy, C. P., & Rose, J. E. (2005) · Experimental and Clinical Psychopharmacology · doi:10.1037/1064-1297.13.3.219 · Cited by 70
Barone, B. B., Wang, N.-Y., Bacher, A. C., & Stewart, K. J. (2009) · British Journal of Sports Medicine · doi:10.1136/bjsm.2008.050906 · Cited by 70
Preisser, J. S. (2003) · American Journal of Epidemiology · doi:10.1093/aje/kwg169 · Cited by 61
Risk factors for persistent Aspergillus respiratory isolation in cystic fibrosis.
Hong, G., Psoter, K. J., Jennings, M. T., Merlo, C. A., Boyle, M. P., Hadjiliadis, D., Kawut, S. M., & Lechtzin, N. (2018) · Journal of Cystic Fibrosis · doi:10.1016/j.jcf.2018.01.008 · Cited by 59
Cavender, M. A., Rassi, A. N., Fonarow, G. C., Cannon, C. P., Peacock, W. F., Laskey, W. K., Hernandez, A. F., Peterson, E. D., Cox, M., Grau‐Sepulveda, M., et al. (2013) · Clinical Cardiology · doi:10.1002/clc.22213 · Cited by 57
Xu, C., Zhou, X., Zorzela, L., Ju, K., Furuya-Kanamori, L., Lin, L., Lu, C., Musa, O. A. H., & Vohra, S. (2021) · BMC Medicine · doi:10.1186/s12916-021-02008-2 · Cited by 43
Zummo, L., Donovan, B., & Busch, K. C. (2021) · Journal of Research in Science Teaching · doi:10.1002/tea.21648 · Cited by 52
Raudenbush, S. W. (2007) · Handbook of Multilevel Analysis · doi:10.1007/978-0-387-73186-5_5 · Cited by 51
Schaub, M., Sullivan, R., Haug, S., & Stark, L. (2012) · Journal of Medical Internet Research · doi:10.2196/jmir.2244 · Cited by 47
Kalichman, S. C., Cain, D., Eaton, L., Jooste, S., & Simbayi, L. C. (2011) · American Journal of Public Health · doi:10.2105/ajph.2011.300236 · Cited by 47
Caleyachetty, A., Lewis, S., McNeill, A., & Leonardi-Bee, J. (2012) · The European Journal of Public Health · doi:10.1093/eurpub/ckr199 · Cited by 46
Artenie, A. A., Bruneau, J., Zang, G., Lespérance, F., Renaud, J., Tremblay, J., & Jutras-Aswad, D. (2015) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2014.11.011 · Cited by 46
Leeners, B., Hengartner, M. P., Rössler, W., Ajdacic-Gross, V., & Angst, J. (2014) · The Journal of Sexual Medicine · doi:10.1111/jsm.12709 · Cited by 46
Leddy, A. M., Underwood, C., Decker, M. R., Mbwambo, J., Likindikoki, S., Galai, N., & Kerrigan, D. (2018) · AIDS and Behavior · doi:10.1007/s10461-018-2156-8 · Cited by 40
Specificity of familial transmission of anxiety and comorbid disorders
Low, N. C. P., Cui, L., & Merikangas, K. R. (2008) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2007.07.002 · Cited by 39
Global Network Organization of the Fetal Functional Connectome
De Asis-Cruz, J., Andersen, N., Kapse, K., Khrisnamurthy, D., Quistorff, J., Lopez, C., Vezina, G., & Limperopoulos, C. (2021) · Cerebral Cortex · doi:10.1093/cercor/bhaa410 · Cited by 40
Kanyangarara, M., Mamini, E., Mharakurwa, S., Munyati, S., Gwanzura, L., Kobayashi, T., Shields, T., Mullany, L. C., Mutambu, S., Mason, P. R., et al. (2016) · PLOS ONE · doi:10.1371/journal.pone.0151971 · Cited by 40
Cropsey, K. L., Schiavon, S., Hendricks, P. S., Froelich, M., Lentowicz, I., & Fargason, R. (2017) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2017.05.024 · Cited by 39
Halim, M. L., Yoshikawa, H., & Amodio, D. M. (2013) · Health Psychology · doi:10.1037/a0027279 · Cited by 36
Lee, S.-Y., Chen, S.-L., Chang, Y.-H., Chen, S.-H., Chu, C.-H., Huang, S.-Y., Tzeng, N.-S., Wang, C.-L., Lee, I. H., Yeh, T. L., et al. (2012) · Journal of Affective Disorders · doi:10.1016/j.jad.2012.01.024 · Cited by 35
Gregg, E. W., Karter, A. J., Gerzoff, R. B., Safford, M., Brown, A. F., Tseng, C.-W., Waitzfielder, B., Herman, W. H., Mangione, C. M., Selby, J. V., et al. (2010) · Medical Care · doi:10.1097/mlr.0b013e3181bd4783 · Cited by 34
Cook’s distance for generalized linear mixed models
Pinho, L. G. B., Nobre, J. S., & Singer, J. M. (2015) · Computational Statistics & Data Analysis · doi:10.1016/j.csda.2014.08.008 · Cited by 34
Massachusetts’ parental consent law and procedural timing among adolescents undergoing abortion
Janiak, E., Fulcher, I. R., Cottrill, A. A., Tantoco, N., Mason, A. H., Fortin, J., Sabino, J., & Goldberg, A. B. (2019) · Obstetrics & Gynecology · doi:10.1097/aog.0000000000003190 · Cited by 31
The Uses and Impacts of Mobile Computing Technology in Hot Spots Policing
Koper, C. S., Lum, C., & Hibdon, J. (2015) · Evaluation Review · doi:10.1177/0193841x16634482 · Cited by 30
Dietary Counseling for High Blood Cholesterol in Families at Risk of Coronary Disease
Moy, T. F., Yanek, L. R., Raqueño, J. V., Bezirdjian, P. J., Blumenthal, R. S., Wilder, L. B., & Becker, D. M. (2001) · Preventive Cardiology · doi:10.1111/j.1520-037x.2001.00543.x · Cited by 29
Artenie, A. A., Bruneau, J., Roy, É., Zang, G., Lespérance, F., Renaud, J., Tremblay, J., & Jutras‐Aswad, D. (2015) · Addiction · doi:10.1111/add.13030 · Cited by 27
Bär Deucher, A., Hengartner, M., Kawohl, W., Konrad, J., Puschner, B., Clarke, E., Slade, M., Del Vecchio, V., Sampogna, G., Égerházi, A., et al. (2016) · European Psychiatry · doi:10.1016/j.eurpsy.2016.02.001 · Cited by 28
Antenatal steroid therapy for fetal lung maturation: is there an association with childhood asthma
Pole, J. D., Mustard, C. A., To, T., Beyene, J., & Allen, A. C. (2009) · Journal of Asthma · doi:10.1080/02770900802262795 · Cited by 27
Nonconvergence, covariance constraints, and class enumeration in growth mixture models.
McNeish, D., Harring, J. R., & Bauer, D. J. (2023) · Psychological Methods · doi:10.1037/met0000456 · Cited by 27
Amsalem, D., Wall, M., Lazarov, A., Markowitz, J. C., Fisch, C. T., LeBeau, M., Hinds, M., Liu, J., Fisher, P. W., Smith, T. E., et al. (2023) · Psychiatric Services · doi:10.1176/appi.ps.20220083 · Cited by 18
Sex differences in sub-clinical psychosis—Results from a community study over 30years
Rössler, W., Hengartner, M. P., Ajdacic-Gross, V., Haker, H., & Angst, J. (2012) · Schizophrenia Research · doi:10.1016/j.schres.2012.04.017 · Cited by 16
Pu, F., Hu, Y., Li, C., Cao, X., Yang, Z., Liu, Y., Zhang, J., Li, X., Yang, Y., Wang, W., et al. (2023) · Environmental Research · doi:10.1016/j.envres.2022.115022 · Cited by 16
Peterson, E. L., Ownby, D. R., & Johnson, C. C. (2003) · Annals of Allergy, Asthma & Immunology · doi:10.1016/s1081-1206(10)61852-2 · Cited by 11
Association between Binge Drug use and Suicide Attempt among People who Inject Drugs
Fournier, C., Ghabrash, M. F., Artenie, A., Roy, E., Zang, G., Bruneau, J., & Jutras-Aswad, D. (2018) · Substance Abuse · doi:10.1080/08897077.2017.1389800 · Cited by 10
Buchman, A. S., Yu, L., Wilson, R. S., Shulman, J. M., Boyle, P. A., & Bennett, D. A. (2014) · BMC Geriatrics · doi:10.1186/1471-2318-14-54 · Cited by 9
“Then we used a series of linear mixed-effects models to examine the association of baseline harm avoidance score with the rate of change in severity of parkinsonism during the study period [22].”
MethodTseng, H.-W., Lu, L.-Y., & Shiue, Y.-L. (2021) · Air Quality, Atmosphere & Health · doi:10.1007/s11869-021-00999-8 · Cited by 9
Clair, V., Musau, A., Mutiso, V., Tele, A., Atkinson, K., Rossa-Roccor, V., Bosire, E., Ndetei, D., & Frank, E. (2022) · International Journal of Mental Health and Addiction · doi:10.1007/s11469-022-00841-x · Cited by 7
Li, H., Wong, C. L., Jin, X., Chong, Y. Y., & Ng, M. S. N. (2024) · Journal of Contextual Behavioral Science · doi:10.1016/j.jcbs.2024.100758 · Cited by 12
Wang, Y., Zang, C., Li, Z., Guo, C. C., Lai, D., & Wei, P. (2026) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1013956 · Cited by 2
Metadata
- Authors
- Zeger, S. L., Liang, K.-Y., & Albert, P. S.
- Venue
- Biometrics
- Publisher
- JSTOR
- Published
- 1988-12
- Volume
- 44
- Issue
- 4
- Pages
- 1049
- ISSN
- 0006-341X (ISSN-L)
- OpenAlex
- W1976566530
- Cited by
- 4,505
- References
- 0
- FWCI
- 13.59
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
