{ "item_title" : "Longitudinal Structural Equation Modeling", "item_author" : [" Todd D. Little", "Noel A. Card "], "item_description" : "This valuable book is now in a fully updated second edition that presents the latest developments in longitudinal structural equation modeling (SEM) and new chapters on missing data, the random intercepts cross-lagged panel model (RI-CLPM), longitudinal mixture modeling, and Bayesian SEM. Emphasizing a decision-making approach, leading methodologist Todd D. Little describes the steps of modeling a longitudinal change process. He explains the big picture and technical how-tos of using longitudinal confirmatory factor analysis, longitudinal panel models, and hybrid models for analyzing within-person change. User-friendly features include equation boxes that translate all the elements in every equation, tips on what does and doesn't work, end-of-chapter glossaries, and annotated suggestions for further reading. The companion website provides data sets for the examples--including studies of bullying and victimization, adolescents' emotions, and healthy aging--along with syntax and output, chapter quizzes, and the book's figures. New to This Edition:*Chapter on missing data, with a spotlight on planned missing data designs and the R-based package PcAux.*Chapter on longitudinal mixture modeling, with Whitney Moore.*Chapter on the random intercept cross-lagged panel model (RI-CLPM), with Danny Osborne.*Chapter on Bayesian SEM, with Mauricio Garnier.*Revised throughout with new developments and discussions, such as how to test models of experimental effects.", "item_img_path" : "https://covers4.booksamillion.com/covers/bam/1/46/255/314/1462553141_b.jpg", "price_data" : { "retail_price" : "93.00", "online_price" : "93.00", "our_price" : "93.00", "club_price" : "93.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }

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