Prima di Memmo, i miei appunti erano sparsi tra mille PDF. Ora uno spazio di lavoro raccoglie tutto in un unico posto, e vedo esattamente cosa mi resta da studiare.
Longitudinal Analysis provides an accessible, application-oriented treatment of introductory and advanced linear models for within-person fluctuation and change. Organized by research design and data type, the text uses in-depth examples to provide a complete description of the model-building process. The core longitudinal models and their extensions are presented within a multilevel modeling framework, paying careful attention to the modeling concerns that are unique to longitudinal data. Written in a conversational style, the text provides verbal and visual interpretation of model equations to aid in their translation to empirical research results. Overviews and summaries, boldfaced key terms, and review questions will help readers synthesize the key concepts in each chapter.
Written for non-mathematically-oriented readers, this text features:
The book opens with the building blocks of longitudinal analysis—general ideas, the general linear model for between-person analysis, and between- and within-person models for the variance and the options within repeated measures analysis of variance. Section 2 introduces unconditional longitudinal models including alternative covariance structure models to describe within-person fluctuation over time and random effects models for within-person change. Conditional longitudinal models are presented in section 3, including both time-invariant and time-varying predictors. Section 4 reviews advanced applications, including alternative metrics of time in accelerated longitudinal designs, three-level models for multiple dimensions of within-person time, the analysis of individuals in groups over time, and repeated measures designs not involving time. The book concludes with additional considerations and future directions, including an overview of sample size planning and other model extensions for non-normal outcomes and intensive longitudinal data.
Class-tested at the University of Nebraska-Lincoln and in intensive summer workshops, this is an ideal text for graduate-level courses on longitudinal analysis or general multilevel modeling taught in psychology, human development and family studies, education, business, and other behavioral, social, and health sciences. The book’s accessible approach will also help those trying to learn on their own. Only familiarity with general linear models (regression, analysis of variance) is needed for this text.
Prima di Memmo, i miei appunti erano sparsi tra mille PDF. Ora uno spazio di lavoro raccoglie tutto in un unico posto, e vedo esattamente cosa mi resta da studiare.
I riassunti di Memmo sono oro puro prima degli esami. Non devo rileggere 800 pagine due settimane prima, solo le parti importanti.
La chat AI mi ha salvato più di una volta la sera prima di un esame. Continuo a chiedere finché non capisco, senza aspettare risposte da un gruppo di studio.
I quiz colpiscono esattamente ciò che devo sapere. Memmo tiene traccia di dove mi blocco, così mi esercito solo su ciò che conta davvero.
Le flashcard con ripetizione spaziata sono magia pura. Memmo sa quando sto per dimenticare qualcosa e me lo ripropone.
I podcast AI sono i miei preferiti. Li ascolto mentre vado a scuola e ripasso senza stare davanti al computer.
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