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Applied Longitudinal Data Analysis
PART I 1. A framework for investigating change over time 2. Exploring Longitudinal Data on Change 3. Introducing the multilevel model for change 4. Doing data analysis with the multilevel mode forExpand
Using SAS PROC MIXED to Fit Multilevel Models, Hierarchical Models, and Individual Growth Models
This paper is written as a step-by-step tutorial that shows how to fit the two most common multilevel models: (a) school effects models, designed for data on individuals nested within naturally occurring hierarchies (e.g., students within classes); and (b) individual growth models,designed for exploring longitudinal data (on individuals) over time. Expand
Maternal correlates of growth in toddler vocabulary production in low-income families.
Investigation of predictors of growth in toddlers' vocabulary production between the ages of 1 and 3 years by analyzing mother-child communication in 108 low-income families indicates large variation in growth across children. Expand
It’s About Time: Using Discrete-Time Survival Analysis to Study Duration and the Timing of Events
This article uses longitudinal data on the career paths of 3,941 special educators as a springboard, and derives maximum likelihood estimators for the parameters of a discrete-time hazard model and shows how the model can befit using standard logistic regression software. Expand
Are Special Educators' Career Paths Special? Results from a 13-Year Longitudinal Study
A statistical methodology relatively new to education—survival analysis—is used to describe the career paths of over 6,600 special education teachers newly hired in Michigan and North CarolinaExpand
QUANTITATIVE METHODS IN PSYCHOLOGY Modeling the Days of Our Lives: Using Survival Analysis When Designing and Analyzing Longitudinal Studies of Duration and the Timing of Events
Psychologists studying whether and when events occur face unique design and analytic difficulties. The fundamental problem is how to handle censored observations, the people for whom the target eventExpand
The design and analysis of longitudinal studies of development and psychopathology in context: statistical models and methodological recommendations.
It is shown that these methods are essential tools for answering questions about life-span developmental processes in both normal and atypical populations and that their proper use will help developmental psychopathologists and others illuminate how important contextual variables contribute to various pathways of development. Expand
Investigating onset, cessation, relapse, and recovery: why you should, and how you can, use discrete-time survival analysis to examine event occurrence.
Using data on the onset of suicide ideation and depression and relapse into cocaine use, discrete-time survival analysis can address questions about onset, cessation, relapse, and recovery. Expand
The Influences of Salaries and "Opportunity Costs" on Teachers' Career Choices: Evidence from North Carolina
Richard Murnane, Judith Singer, and John Willett analyze data from a larger study on the factors influencing career paths of teachers, focusing specifically on the career paths of White teachers inExpand
It’s Déjà Vu All Over Again: Using Multiple-Spell Discrete-Time Survival Analysis
Multiple-spell discrete-time survival analysis can be used to investigate the repeated occurrence of a single event, or the sequential occurrence of disparate events, including: students’ andExpand