Shu Xu
Shu Xu
Clinical Assistant Professor of Biostatistics
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Professional overview
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Dr. Shu Xu’s work represents a balance of both statistical and applied aspects of quantitative methodology. Her primary quantitative interests include evaluating and developing statistical methods for longitudinal data analysis. Specifically, Dr. Xu’s research focuses on various aspects of latent growth models, missing data methods, and causal inference models.
Dr. Xu has collaborated with substance use, family, and health researchers to advance and share her knowledge of quantitative methodology and pursue a better understanding of the social sciences and public health. She has conducted research with the Family Translational Research Group at NYU and the Methodology Center at the Pennsylvania State University.
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Education
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BS, Psychology, East China Normal University, Shanghai, ChinaMS, Quantitative Psychology, University of California, DavisPhD, Quantitative Psychology, University of California, Davis
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Areas of research and study
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BiostatisticsFamily researchLongitudinal Data AnalysisMissing Data MethodsMixture ModelsQuantitative Research
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Publications
Publications
Cannabis Use and the Onset of Cigarette and E-cigarette Use: A Prospective, Longitudinal Study among Youth in the United States
AbstractWeinberger, A. H., Zhu, J., Lee, J., Xu, S., & Goodwin, R. D.Publication year
2021Journal title
Nicotine and Tobacco ResearchVolume
23Issue
3Page(s)
609-613AbstractIntroduction: Cigarette use is declining among youth in the United States, whereas cannabis use and e-cigarette use are increasing. Cannabis use has been linked with increased uptake and persistence of cigarette smoking among adults. The goal of this study was to examine whether cannabis use is associated with the prevalence and incidence of cigarette, e-cigarette, and dual product use among U.S. youth. Methods: Data included U.S. youth ages 12-17 from two waves of the Population Assessment of Tobacco and Health (PATH) Study (Wave 1 youth, n = 13 651; Wave 1 tobacco-naive youth, n = 10 081). Weighted logistic regression models were used to examine the association between Wave 1 cannabis use and (1) Wave 1 prevalence of cigarette/e-cigarette use among Wave 1 youth and (2) Wave 2 incidence of cigarette/e-cigarette use among Wave 1 tobacco-naive youth. Analyses were run unadjusted and adjusted for demographics and internalizing/externalizing problem symptoms. Results: Wave 1 cigarette and e-cigarette use were significantly more common among youth who used versus did not use cannabis. Among Wave 1 tobacco-naive youth, Wave 1 cannabis use was associated with significantly increased incidence of cigarette and e-cigarette use by Wave 2. Conclusions: Youth who use cannabis are more likely to report cigarette and e-cigarette use, and cannabis use is associated with increased risk of initiation of cigarette and e-cigarette use over 1 year. Continued success in tobacco control-specifically toward reducing smoking among adolescents-may require focusing on cannabis, e-cigarette, and cigarette use in public health education, outreach, and intervention efforts. Implications: These data extend our knowledge of cigarette and e-cigarette use among youth by showing that cannabis use is associated with increased prevalence and incidence of cigarette and e-cigarette use among youth, relative to youth who do not use cannabis. The increasing popularity of cannabis use among youth and diminished perceptions of risk, coupled with the strong link between cannabis use and tobacco use, may have unintended consequences for cigarette control efforts among youth.E-cigarette use, systemic inflammation, and depression
AbstractFarrell, K. R., Karey, E., Xu, S., Gibbon, G., Gordon, T., & Weitzman, M.Publication year
2021Journal title
International journal of environmental research and public healthVolume
18Issue
19AbstractBackground: E-cigarette use (vaping) is an emerging public health problem. Depression has been found to be associated with e-cigarette use, and vaping and depression are each associated with elevated systemic inflammation. To date, the role of inflammation in the relationship between vaping and depression has not been explored. Objective: To assess the independent associations between e-cigarette use, depression, and inflammation, and to investigate whether the likelihood of depression among current e-cigarette users is associated with systemic inflammation. Methods: Nationally representative NHANES data from 2015–2018 were used (n = 4961). Systemic inflammation was defined as serum C-reactive protein (CRP) ≥ 8.0 mg/L. Depressed individuals were characterized by a score ≥ 10 on the Patient Health Questionnaire-9 (PHQ-9). Current e-cigarette users were defined as individuals who vaped at least once in the past 30 days and these individuals were stratified by use: exclusive users (reported smoking less than 100 combustible cigarettes in their lifetime), dual users (reported current use of electronic and combustible cigarettes), and e-cigarette users who were previous smokers. Bivariate analyses were used to assess independent associations between vaping, depression, and inflammation; and weighted logistic regression analyses adjusting for BMI, sex, and economic status were used to determine the odds ratios (ORs) for depression by e-cigarette category stratified by differential CRP levels. Results: Depression occurred in 16.7% of all e-cigarette users vs. 5.0% of those who never used e-cigarettes (p < 0.001). In adjusted analyses, the following elevated ORs were found: all current e-cigarette users with CRP <8 = 3.37 (95% CI: 2.06, 5.51) vs. CRP ≥8 = 6.70 (2.48, 18.11); exclusive e-cigarette users with CRP <8 = 1.91 (0.78, 4.69) vs. those with CRP ≥8 = 5.09 (1.44, 18.02); and dual users with CRP <8 = 4.31 (2.35, 7.89) vs. those with CRP ≥8 = 7.37 (1.85, 29.41). These ORs indicate that depression is associated with each category of e-cigarette use; however, we found this association did not vary by systemic inflammation level (interaction p-values > 0.05). Conclusion: While a pattern of greater ORs for depression among e-cigarette users with elevated CRP provides provocative findings that might suggest a potential role of inflammation in the association between vaping and depression, we failed to find evidence that inflammation clearly moderates this association. While it is possible that depression among e-cigarette users may be influenced by systemic inflammation, a reproduction of the current study is necessary among a larger cohort to elucidate the effect of inflammation on depression among e-cigarette users.Relationships Between E-cigarette Use and Subsequent Cigarette Initiation Among Adolescents in the PATH Study: an Entropy Balancing Propensity Score Analysis
AbstractXu, S., Coffman, D. L., Liu, B., Xu, Y., He, J., & Niaura, R. S.Publication year
2022Journal title
Prevention ScienceVolume
23Issue
4Page(s)
608-617AbstractThis study aimed to examine the relationship between electronic cigarette use and subsequent combustible cigarette use, controlling for confounding by using a propensity score method approach. Data from the first three annual waves of the Population Assessment of Tobacco and Health study were analyzed (n = 6309). Participants were tobacco-naïve at Wave 1; used e-cigarettes exclusively (n = 414), used combustible cigarettes exclusively (n = 46), or not used any tobacco products (n = 5849) at Wave 2. We conducted entropy balancing propensity score analysis to examine the association between exclusive e-cigarette or cigarette initiation and subsequent cigarette use at Wave 3, adjusting for non-response bias, sampling bias, and confounding. Among tobacco-naïve youth, exclusive e-cigarette use was associated with greater risk for subsequent combustible cigarette smoking initiation (OR = 3.42, 95% CI = (1.99, 5.93)) and past 30-day combustible cigarette use (OR = 2.88, 95% CI = (1.22, 6.86)) in the following year. However, the latter risk was comparatively lower than the risk if youth started with a combustible cigarette (OR = 25.79, 95% CI = (9.68, 68.72)). Results of sensitivity analyses indicated that estimated effects were robust to unmeasured confounding. Use of e-cigarettes in tobacco-naïve youth is associated with increased risk of subsequent past 30-day combustible cigarette use but the risk is an order of magnitude higher if they start with a combustible cigarette.Self-report measures of coercive process in couple and parent–child dyads.
AbstractMitnick, D. M., Lorber, M. F., Smith Slep, A. M., Heyman, R. E., Xu, S., Bulling, L. J., Nichols, S. R., & Eddy, J. M.Publication year
2021Journal title
Journal of Family PsychologyVolume
35Issue
3Page(s)
388-398AbstractOne of the most influential behavioral models of family conflict is G. R. Patterson’s (1982) coercive family process theory. Self-reports for behaviors related to coercion (e.g., hostility toward a family member) abound; however, there are no self-report measures for coercive process itself, which is, by definition, a dyadic process. Operationalizations of coercive process are measured with behavioral observation, typically including sequential analyzed, microcoded behaviors. Despite its objectivity and rigor, coding of behavior observation is not always feasible in research and applied settings because of the high training, personnel, and time costs the observation requires. Because coercive process has been shown to predict a host of maladaptive outcomes (e.g., parent–child conflict, aggression, negative health outcomes) and given the complete absence of self-report measures of coercive process, we recently designed brief questionnaires to assess coercive process in couple (Couple Coercive Process Scale [CCPS]) and parent–child interactions (Parent–Child Coercive Process Scale [PCCPS]) and tested them via Qualtrics participant panels in samples recruited to mirror socioeconomic generalizability to U.S. Census data. The CCPS and PCCPS exhibited initial evidence of psychometric quality in measuring coercive process in couple and parent–child dyads: Both measures are unifactorial; have evidence of reliability, especially at higher levels of coercive process; and demonstrate concurrent validity with constructs in their nomological networks, with medium to large effect sizes. (PsycInfo Database Record (c) 2021 APA, all rights reserved)High Sensitivity and Specificity Screening for Clinically Significant Intimate Partner Violence
AbstractHeyman, R. E., Baucom, K. J., Xu, S., Smith Slep, A. M., Snarr, J. D., Foran, H. M., Lorber, M. F., Wojda, A. K., & Linkh, D. J.Publication year
2020Journal title
Journal of Family PsychologyAbstractThe U.S. Preventive Services Task Force has recommended that clinicians screen patients for intimate partner violence (IPV). This article aims to develop and test the first screeners for clinically significant physical and psychological IPV (i.e., acts meeting criteria in the International Classification of Diseases (11th ed.; ICD-11; World Health Organization, 2019) and the Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5; American Psychiatric Association, 2013). The goal was to derive screeners that (1) are maximally brief, while still achieving high sensitivity and specificity; (2) assess perpetration and victimization when either men or women are reporting; and (3) use ICD-11/DSM-5 criteria as the reference standard. Random samples of active duty service members at 82 installations worldwide were obtained via e-mail invitation (2006: N = 54,543; 2008: N = 48,909); their response rates were excellent for long general population surveys with no payment (2006: 44.7%, 2008: 49.0%). The population of spouses at the participating installation was invited by mailed postcard (2006: N = 19,722; 2008: N = 12,127; response rates-2006: 12.3%, 2008: 10.8%). Clinically significant physical intimate partner violence can be effectively screened with as few as four items, with sensitivities >90% and specificities >95%; clinically significant psychological intimate partner violence can be screened with two items. Men and women can be screened with equivalent accuracy, as can those committing the violence and those victimized by it.Psychology of wearing face masks to prevent transition of COVID-19
Song, L. J., Xu, S., Xu, S. L., Sun, Z., & Liu, W.Publication year
2020Journal title
General PsychiatryVolume
33Issue
6The lump-versus-split dilemma in couple observational coding: A multisite analysis of rapid marital interaction coding system data.
AbstractHeyman, R. E., Otto, A. K., Reblin, M., Wojda, A. K., & Xu, S.Publication year
2020Journal title
Journal of Family PsychologyAbstractHistorically, observational couple communication researchers have oscillated between splitting behaviors into narrowly defined discrete codes and grouping behaviors into broader codes—sometimes within the same study. We label this the “lump-versus-split dilemma.” Coding across a decade and 11 investigators were used to recommend the most meaningful number of codes to use when observing couples’ conflict. We combined data from 14 studies that used the Rapid Marital Interaction Coding System (RMICS) to score communication behavior during different-sex couples’ conflict interactions. In each study, couples completed at least one 10-min, video-recorded conflict discussion. Communication during these interactions was coded by trained research staff using RMICS; all codes were compiled into a single data set for descriptive analysis and exploratory factor analyses (EFAs). The final sample comprised N = 2,011 couples. Several RMICS codes were extremely infrequent—specifically, distress-maintaining attributions, psychological abuse, withdrawal, dysphoric affect, and relationship-enhancing attributions. By far, the most frequent code was constructive problem discussion. EFAs yielded two factors for both women and men. Factor 1 (Negative) contained two items: distress-maintaining attributions and hostility. Factor 2 (Nonnegative) contained constructive problem discussion and humor (and, for women only, acceptance). Results side heavily with the “lump” camp in the lump-versus-split dilemma in couple observational coding. These RMICS factor analysis results converge with those from other systems and imply that the microanalytic “splitting” era in couples coding should draw to a close, with future studies instead focused on negative, neutral, and positive codes. (PsycInfo Database Record (c) 2020 APA, all rights reserved)Using Security Questions to Link Participants in Longitudinal Data Collection
AbstractXu, S., Chan, A., Lorber, M. F., & Chase, J. P.Publication year
2020Journal title
Prevention ScienceVolume
21Issue
2Page(s)
194-202AbstractAnonymous data collection systems are often necessary when assessing sensitive behaviors but can pose challenges to researchers seeking to link participants over time. To assist researchers in anonymously linking participants, we outlined and tested a novel security question linking (security question linking; SEEK) method. The SEEK method includes four steps: (1) data management and standardization, (2) many-to-many matching, (3) fuzzy matching, and (4) rematching and verification. The method is demonstrated in SAS with two samples from a longitudinal study of adolescent dating violence. After an initial assessment during a laboratory visit, participants were asked to complete an online assessment either (a) once, 3 months later (Sample 1, n = 60), or (b) three times at 1-month intervals (Sample 2, n = 140). Demographics, eye color, and responses to nine security questions were used as key variables to link responses from the laboratory and online follow-up assessments. The rates of matched cases were 100% in Sample 1 and from 94.3 to 98.3% in Sample 2. To quantify the confidence in the data quality of successfully matched pairs, we reported the means and standard deviations of the number of matched security questions. In addition, we reported the rank order and counts of the mismatched components in key variables. Results indicate that the SEEK method provides a feasible and reliable solution to link responses in longitudinal studies with sensitive questions.A Randomized, Controlled Trial of the Impact of the Couple CARE for Parents of Newborns Program on the Prevention of Intimate Partner Violence and Relationship Problems
AbstractHeyman, R. E., Slep, A. M., Lorber, M. F., Mitnick, D. M., Xu, S., Baucom, K. J., Halford, W. K., & Niolon, P. H.Publication year
2019Journal title
Prevention ScienceVolume
20Issue
5Page(s)
620-631AbstractEffective, accessible prevention programs are needed for adults at heightened risk for intimate partner violence (IPV). This parallel group randomized controlled trial examines whether such couples receiving the American version of Couple CARE for Parents of Newborns (CCP; Halford et al. 2009) following the birth of a child, compared with controls, report fewer first occurrences of clinically significant IPV, less frequent physical and psychological IPV, and improved relationship functioning. Further, we test whether intervention effects are moderated by level of risk for IPV. Couples at elevated risk for IPV (N = 368) recruited from maternity units were randomized to CCP (n = 188) or a 24-month waitlist (n = 180) and completed measures of IPV and relationship functioning at baseline, post-program (when child was 8 months old), and two follow-ups (at 15 and 24 months). Intervention effects were tested using intent to treat (ITT) as well as complier average causal effect (CACE; Jo and Muthén 2001) structural equation models. CCP did not significantly prevent clinically significant IPV nor were there significant main effects of CCP on clinically significant IPV, frequency of IPV, or most relationship outcomes in the CACE or ITT analyses. Risk moderated the effect of CCP on male-to-female physical IPV at post-program, with couples with a planned pregnancy declining, but those with unplanned pregnancies increasing. This study adds to previous findings that prevention programs for at-risk couples are not often effective and may even be iatrogenic for some couples.Patterns of psychological health problems and family maltreatment among United States Air Force members
AbstractLorber, M. F., Xu, S., Heyman, R. E., Slep, A. M., & Beauchaine, T. P.Publication year
2018Journal title
Journal of Clinical PsychologyVolume
74Issue
7Page(s)
1258-1271AbstractObjectives:: We sought to identify subgroups of individuals based on patterns of psychological health problems (PH; e.g., depressive symptoms, hazardous drinking) and family maltreatment (FM; e.g., child and partner abuse). Method:: We analyzed data from very large surveys of United States Air Force active duty members with romantic partners and children. Results:: Latent class analyses indicated six replicable patterns of PH problems and FM. Five of these classes, representing ∼98% of survey participants, were arrayed ordinally, with increasing risk of multiple PH problems and FM. A sixth group defied this ordinal pattern, with pronounced rates of FM and externalizing PH problems, but without correspondingly high rates/levels of internalizing PH problems. Conclusions:: Ramifications of these results for intervention are discussed.A New Look at the Psychometrics of the Parenting Scale Through the Lens of Item Response Theory
AbstractLorber, M. F., Xu, S., Slep, A. M., Bulling, L., & O’Leary, S. G.Publication year
2014Journal title
Journal of Clinical Child and Adolescent PsychologyVolume
43Issue
4Page(s)
613-626AbstractThe psychometrics of the Parenting Scale's Overreactivity and Laxness subscales were evaluated using item response theory (IRT) techniques. The IRT analyses were based on 2 community samples of cohabiting parents of 3- to 8-year-old children, combined to yield a total sample size of 852 families. The results supported the utility of the Overreactivity and Laxness subscales, particularly in discriminating among parents in the mid to upper reaches of each construct. The original versions of the Overreactivity and Laxness subscales were more reliable than alternative, shorter versions identified in replicated factor analyses from previously published research and in IRT analyses in the present research. Moreover, in several cases, the original versions of these subscales, in comparison with the shortened versions, exhibited greater 6-month stabilities and correlations with child externalizing behavior and couple relationship satisfaction. Reliability was greater for the Laxness than for the Overreactivity subscale. Item performance on each subscale was highly variable. Together, the present findings are generally supportive of the psychometrics of the Parenting Scale, particularly for clinical research and practice. They also suggest areas for further development.Interrater agreement statistics with skewed data: Evaluation of alternatives to Cohen's kappa
AbstractXu, S., & Lorber, M. F.Publication year
2014Journal title
Journal of consulting and clinical psychologyVolume
82Issue
6Page(s)
1219-1227AbstractObjective: In this study, we aimed to evaluate interrater agreement statistics (IRAS) for use in research on low base rate clinical diagnoses or observed behaviors. Establishing and reporting sufficient interrater agreement is essential in such studies. Yet the most commonly applied agreement statistic, Cohen's, has a well known sensitivity to base rates that results in a substantial penalization of interrater agreement when behaviors or diagnoses are very uncommon, a prevalent and frustrating concern in such studies. Method: We performed Monte Carlo simulations to evaluate the performance of 5 of κ's alternatives (Van Eerdewegh's V, Yule's Y, Holley and Guilford's G, Scott's π, and Gwet's AC1), alongside κ itself. The simulations investigated the robustness of these IRAS to conditions that are common in clinical research, with varying levels of behavior or diagnosis base rate, rater bias, observed interrater agreement, and sample size. Results: When the base rate was 0.5, each IRAS provided similar estimates, particularly with unbiased raters. G was the least sensitive of the IRAS to base rates. Conclusions: The results encourage the use of the G statistic for its consistent performance across the simulation conditions. We recommend separately reporting the rates of agreement on the presence and absence of a behavior or diagnosis alongside G as an index of chance corrected overall agreement.Noxious family environments in relation to adult and childhood caries
AbstractLorber, M. F., Slep, A. M., Heyman, R. E., Xu, S., Dasanayake, A. P., & Wolff, M. S.Publication year
2014Journal title
Journal of the American Dental AssociationVolume
145Issue
9Page(s)
924-930AbstractBackground. The authors tested hypotheses that more noxious family environments are associated with poorer adult and child oral health. Methods. A community sample of married or cohabiting couples (N = 135) and their elementary school-aged children participated. Dental hygienists determined the number of decayed, missing and filled surfaces via oral examination. Subjective oral health impacts were measured by means of questionnaires completed by the parents and children. The parents completed questionnaires about interparental and parent-to-child physical aggression (for example, pushing) and emotional aggression (for example, derision), as well as harsh discipline. Observers rated the couples' hostile behavior in laboratory interactions. Results. The extent of women's and men's caries experience was associated positively with their partners' levels of overall noxious behavior toward them. The extent of children's caries experience was associated positively with the level of their mothers' emotional aggression toward their partners. Conclusions. Noxious family environments may be implicated in compromised oral health. Future research that replicates and extends these findings can provide the foundation to translate them into preventive interventions. Practical Implications. Noxious family environments may help explain the limitations of routine oral health preventive strategies. Interprofessional strategies that also address the family environment ultimately may prove to be more effective than are single modality approaches.On Fitting a Multivariate Two-Part Latent Growth Model
AbstractXu, S., Blozis, S. A., & Vandewater, E. A.Publication year
2014Journal title
Structural Equation ModelingVolume
21Issue
1Page(s)
131-148AbstractA 2-part latent growth model can be used to analyze semicontinuous data to simultaneously study change in the probability that an individual engages in a behavior, and if engaged, change in the behavior. This article uses a Monte Carlo (MC) integration algorithm to study the interrelationships between the growth factors of 2 variables measured longitudinally where each variable can follow a 2-part latent growth model. A SAS macro implementing Mplus is developed to estimate the model to take into account the sampling uncertainty of this simulation-based computational approach. A sample of time-use data is used to show how maximum likelihood estimates can be obtained using a rectangular numerical integration method and an MC integration method.Causal Inference in Latent Class Analysis
AbstractLanza, S. T., Coffman, D. L., & Xu, S.Publication year
2013Journal title
Structural Equation ModelingVolume
20Issue
3Page(s)
361-383AbstractThe integration of modern methods for causal inference with latent class analysis (LCA) allows social, behavioral, and health researchers to address important questions about the determinants of latent class membership. In this article, 2 propensity score techniques, matching and inverse propensity weighting, are demonstrated for conducting causal inference in LCA. The different causal questions that can be addressed with these techniques are carefully delineated. An empirical analysis based on data from the National Longitudinal Survey of Youth 1979 is presented, where college enrollment is examined as the exposure (i.e., treatment) variable and its causal effect on adult substance use latent class membership is estimated. A step-by-step procedure for conducting causal inference in LCA, including multiple imputation of missing data on the confounders, exposure variable, and multivariate outcome, is included. Sample syntax for carrying out the analysis using SAS and R is given in an appendix.Preadolescent drug use resistance skill profiles, substance use, and substance use prevention
AbstractHopfer, S., Hecht, M. L., Lanza, S. T., Tan, X., & Xu, S.Publication year
2013Journal title
Journal of Primary PreventionVolume
34Issue
6Page(s)
395-404AbstractThe aims of the current study were threefold: (1) specify the skills component of social influence prevention interventions for preadolescents, (2) examine the relationship between resistance skill profiles and substance use among preadolescents, and (3) evaluate whether subgroups of preadolescents based on their resistance skills and refusal confidence may be differentially impacted by the kiR prevention program. Latent class analysis showed a four-class model of 5th grader resistance skill profiles. Approximately half of preadolescents (53 %) were familiar with four prototypical resistance skills and showed confidence to apply these skills in real-world settings (highly competent profile); 15 % were familiar with resistance skills but had little confidence (skillful profile); 18 % were confident yet had little knowledge (confident profile); while 15 % had low knowledge and confidence (low competence profile). These skill profiles significantly predicted 8th grade recent substance use (2LL = -2,262.21, df = 3, p = .0005). As predicted by theory, the highly competent skill profile reported lower mean recent substance use than the population sample mean use. Latent transition analysis showed that although patterns of transiting into the highly competent skill profile over time were observed in the expected direction, this pattern was not significant when comparing treatment and control. Identifying skill profiles that predict recent substance use is theoretically consistent and has important implications for healthy and substance-free development.Sensitivity Analysis of Multiple Informant Models When Data Are Not Missing at Random
AbstractBlozis, S. A., Ge, X., Xu, S., Natsuaki, M. N., Shaw, D. S., Neiderhiser, J. M., Scaramella, L. V., Leve, L. D., & Reiss, D.Publication year
2013Journal title
Structural Equation ModelingVolume
20Issue
2Page(s)
283-298AbstractMissing data are common in studies that rely on multiple informant data to evaluate relationships among variables for distinguishable individuals clustered within groups. Estimation of structural equation models using raw data allows for incomplete data, and so all groups can be retained for analysis even if only 1 member of a group contributes data. Statistical inference is based on the assumption that data are missing completely at random or missing at random. Importantly, whether or not data are missing is assumed to be independent of the missing data. A saturated correlates model that incorporates correlates of the missingness or the missing data into an analysis and multiple imputation that might also use such correlates offer advantages over the standard implementation of SEM when data are not missing at random because these approaches could result in a data analysis problem for which the missingness is ignorable. This article considers these approaches in an analysis of family data to assess the sensitivity of parameter estimates and statistical inferences to assumptions about missing data, a strategy that could be easily implemented using SEM software.Sensitivity analysis of mixed models for incomplete longitudinal data
AbstractXu, S., & Blozis, S. A.Publication year
2011Journal title
Journal of Educational and Behavioral StatisticsVolume
36Issue
2Page(s)
237-256AbstractMixed models are used for the analysis of data measured over time to study population-level change and individual differences in change characteristics. Linear and nonlinear functions may be used to describe a longitudinal response, individuals need not be observed at the same time points, and missing data, assumed to be missing at random (MAR), may be handled. While the mechanism giving rise to the missing data cannot be determined by the observations, the sensitivity of parameter estimates to missing data assumptions can be studied, for example, by fitting multiple models that make different assumptions about the missing data process. Sensitivity analysis of a mixed model that may include nonlinear parameters when some data are missing is discussed. An example is provided.Latent curve models: A structural equation perspective
Blozis, S. A., Cho, Y., & Xu, V. S.Publication year
2010Journal title
Sociological Methods and ResearchVolume
39Page(s)
297The belief and modeling of aging
Cui, L. J., Xu, V. S., & Wang, X. J.Publication year
2000Journal title
Chinese Journal of GerontologyVolume
20Page(s)
3A study on the relationship between adaptive ability and home environment in middle school
Li, G., & Xu, V. S.Publication year
1999Journal title
In Learning and ResearchPage(s)
45