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Rioux, Charlie; Little, Todd D. – International Journal of Behavioral Development, 2021
Missing data are ubiquitous in studies examining preventive interventions. This missing data need to be handled appropriately for data analyses to yield unbiased results. After a brief discussion of missing data mechanisms, inappropriate missing data treatments and appropriate missing data treatments, we review the current state of missing data…
Descriptors: Prevention, Intervention, Data Analysis, Correlation
Little, Todd D.; Chang, Rong; Gorrall, Britt K.; Waggenspack, Luke; Fukuda, Eriko; Allen, Patricia J.; Noam, Gil G. – International Journal of Behavioral Development, 2020
We revisit the merits of the retrospective pretest-posttest (RPP) design for repeated-measures research. The underutilized RPP method asks respondents to rate survey items twice during the same posttest measurement occasion from two specific frames of reference: "now" and "then." Individuals first report their current attitudes…
Descriptors: Pretesting, Alternative Assessment, Program Evaluation, Evaluation Methods
Rioux, Charlie; Stickley, Zachary L.; Little, Todd D. – International Journal of Behavioral Development, 2021
Following the onset of the novel coronavirus disease 2019 (COVID-19) pandemic, daily life significantly changed for the population. Accordingly, researchers interested in examining patterns of change over time may now face discontinuities around the pandemic. Researchers collecting in-person longitudinal data also had to cancel or delay data…
Descriptors: Longitudinal Studies, COVID-19, Pandemics, Simulation
Rhemtulla, Mijke; Jia, Fan; Wu, Wei; Little, Todd D. – International Journal of Behavioral Development, 2014
We examine the performance of planned missing (PM) designs for correlated latent growth curve models. Using simulated data from a model where latent growth curves are fitted to two constructs over five time points, we apply three kinds of planned missingness. The first is item-level planned missingness using a three-form design at each wave such…
Descriptors: Data Analysis, Error of Measurement, Models, Longitudinal Studies
Jia, Fan; Moore, E. Whitney G.; Kinai, Richard; Crowe, Kelly S.; Schoemann, Alexander M.; Little, Todd D. – International Journal of Behavioral Development, 2014
Utilizing planned missing data (PMD) designs (ex. 3-form surveys) enables researchers to ask participants fewer questions during the data collection process. An important question, however, is just how few participants are needed to effectively employ planned missing data designs in research studies. This article explores this question by using…
Descriptors: Data Analysis, Statistical Inference, Error of Measurement, Computation
Lang, Kyle M.; Little, Todd D. – International Journal of Behavioral Development, 2014
We present a new paradigm that allows simplified testing of multiparameter hypotheses in the presence of incomplete data. The proposed technique is a straight-forward procedure that combines the benefits of two powerful data analytic tools: multiple imputation and nested-model ?2 difference testing. A Monte Carlo simulation study was conducted to…
Descriptors: Hypothesis Testing, Data Analysis, Error of Measurement, Computation
Garnier-Villarreal, Mauricio; Rhemtulla, Mijke; Little, Todd D. – International Journal of Behavioral Development, 2014
We examine longitudinal extensions of the two-method measurement design, which uses planned missingness to optimize cost-efficiency and validity of hard-to-measure constructs. These designs use a combination of two measures: a "gold standard" that is highly valid but expensive to administer, and an inexpensive (e.g., survey-based)…
Descriptors: Longitudinal Studies, Data Analysis, Error of Measurement, Research Problems