Applied Longitudinal Data Analysis Modeling Change And Event Occurrence

By T. Gerber. 2016

3,917 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/0ac0025529c1f9056036be43c561ba67fb8d12a5

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Citations in the corpus

Trajectories of Adolescent Alcohol Use by Gender and Early Initiation Status (2016, methodology): “Specifically, we model adolescent alcohol trajectories using a growth curve framework (Singer & Willett, 2003) as a function of early initiation status and gender.”
Social and Emotional Learning in Adolescence: Testing the CASEL Model in a Normative Sample (2018, methodology): “Maximum likelihood parameter estimates (MLR) were used in the Mplus analysis to account for missing data, which allows full use of the data available, making analysis possible even if participants vary in the number or spacing between data points (Cillessen & Borch, 2006; Singer & Willett, 2003).”
Using an Ever–English Learner Framework to Examine Disproportionality in Special Education (2017, methodology): “First, we included only students’ first observed test scores to minimize endogeneity (Singer & Willett, 2003).”
Studying Changes in Life Circumstances and Personality: It's about Time (2014, methodology): “By using statistical techniques such as growth curve modelling, it is relatively straightforward to model non-linear change (Grimm & Ram, 2009; Ram & Grimm, 2007), discontinuous (or piecewise) change (Kim & Kim, 2012; Singer & Willett, 2003), and the combination of the two.”
Leader reactions to follower proactive behavior: Giving credit when credit is due (2015, methodology): “The five control variables were treated as fixed in order to build a more parsimonious model (Singer and Willett, 2003).”
Math Shelf: A Randomized Trial of a Prekindergarten Tablet Number Sense Curriculum (2016, methodology): “Standard longitudinal linear mixed effects modeling (e.g., Singer & Willett, 2003) was used to test the change from the pre- to postintervention.”
A practical guide to the analysis of non-response and attrition in longitudinal research using a real data example (2018, background): “Non-random participation and attrition, whereby presence in a research sample at a given wave is directly or indirectly related to the characteristics under study, represent important challenges for such studies (e.g., Singer & Willet, 2003).”
Lunch Breaks Unpacked: The Role of Autonomy as a Moderator of Recovery during Lunch (2014, background): “Only those who completed at least three daily surveys and had matching coworker evaluations were included in the final sample (see Singer & Willett, 2003).”
When passion fades: disentangling the temporal dynamics of entrepreneurial passion for founding (2016, background): “Modelling change typically consists of two steps (e.g., Singer and Willett, 2003).”
Relating Latent Change Score and Continuous Time Models (2015, unknown): “This, for example, is the case in latent growth curve models (Bollen & Curran, 2006; Duncan, Duncan, & Strycker, 2006) or multilevel/mixed-effects models (Hox, 2010; Pinheiro & Bates, 2000; Singer & Willett, 2003).”
Getting to Know You (2017, unknown): “…the middle period of socialization, it also represents an advantage of the study as longitudinal research that collects data in waves that are spread away from the midpoint of the data collection period offer greater reliability and precision in their measurement of change (Singer & Willett, 2003).”
An Examination of the Efficacy of Insights in Enhancing the Academic and Behavioral Development of Children in Early Grades. (2014, unknown): “Individual growth modeling allows one to model change over time in an outcome with repeated measures (Singer & Willett, 2003).”
Design-Comparable Effect Sizes in Multiple Baseline Designs (2014, methodology): “We write the models using a two-level formulation similar to that used by Singer and Willett (2003), where Level 1 (the within-case level) describes a regression model for the ith individual and Level 2 (the between-case level) describes how the within-case regression coefficients vary across cases.”
Empirics in Family Business Research (2016, background): “Indeed, the complex nature of time and its effects on organizations has led to the development of a variety of empirical approaches including hazard modeling (Bronnenberg & Mela, 2004), growth modeling (Bliese & Ployhart, 2002), and discontinuous change modeling (Singer & Willett, 2003).”
Malleability, plasticity, and individuality: How children learn and develop in context1 (2019, background): “…complexity, particularly when such methods address intersectionality (Fischer & Kennedy, 1997; Hartelman, van der Maas, & Molenaar, 1998; Singer & Willett, 2003; van Geert, 1991, 2003) and do not generalize findings to all human beings or all members of a group (M. Cole, 1996, Fischer &…”
Effects of Self-Esteem and Narcissism on Bullying and Victimization During Early Adolescence (2015, background): “However, the 1-year follow-up time might be considered to be a limitation, as additional time points of measurement would have allowed the investigation of trajectories of change over time in bullying and victimization (Singer & Willett, 2003).”
School District Educational Infrastructure and Change at Scale: Teacher Peer Interactions and Their Beliefs About Mathematics Instruction (2017, methodology): “…to whether teachers’ beliefs were associated with the beliefs of peers with whom they interact by fitting multilevel growth models for change using a person-period data set (i.e., Level 1 was within-teacher change over time; Level 2 was between-teacher change across years; Singer & Willett, 2003).”
Team Microdynamics: Toward an Organizing Approach to Teamwork (2014, background): “…Raudenbush, & Bryk, 2002; Snijders & Bosker, 1999), books on longitudinal data analysis that include multilevel approaches (Hedeker & Gibbons, 2006; Singer & Willett, 2003), books that provide guidance with implementations in SAS (Littell, Milliken, Stroup, Wolfinger, & Schabenberger, 2006), in…”
Minding the Gap (2016, background): “…(i.e., trends) for each firm allow us to observe the direction of performance over time, thereby providing more detail about firm-level changes in performance than that which would be provided by simple averages or snapshots of performance at any one point in time (Singer & Willett, 2003).”