abstract: Designing studies that use latent growth modeling to investigate change over time calls for optimal approaches for conducting power analysis for a priori determination of required sample size. This investigation (1) studied the impacts of variations in specified parameters, design features, and model misspecification in simulation-based power analyses and (2) compared power estimates across three common power analysis techniques: the Monte Carlo method; the Satorra-Saris method; and the method developed by MacCallum, Browne, and Cai (MBC). Choice of sample size, effect size, and slope variance parameters markedly influenced power estimates; however, level-1 error variance and number of repeated measures (3 vs. 6) when study length was held constant had little impact on resulting power. Under some conditions, having a moderate versus small effect size or using a sample size of 800 versus 200 increased power by approximately .40, and a slope variance of 10 versus 20 increased power by up to .24. Decreasing error variance from 100 to 50, however, increased power by no more than .09 and increasing measurement occasions from 3 to 6 increased power by no more than .04. Misspecification in level-1 error structure had little influence on power, whereas misspecifying the form of the growth model as linear rather than quadratic dramatically reduced power for detecting differences in slopes. Additionally, power estimates based on the Monte Carlo and Satorra-Saris techniques never differed by more than .03, even with small sample sizes, whereas power estimates for the MBC technique appeared quite discrepant from the other two techniques. Results suggest the choice between using the Satorra-Saris or Monte Carlo technique in a priori power analyses for slope differences in latent growth models is a matter of preference, although features such as missing data can only be considered within the Monte Carlo approach. Further, researchers conducting power analyses for slope differences in latent growth models should pay greatest attention to estimating slope difference, slope variance, and sample size. Arguments are also made for examining model-implied covariance matrices based on estimated parameters and graphic depictions of slope variance to help ensure parameter estimates are reasonable in a priori power analysis. / Dissertation/Thesis / Ph.D. Educational Psychology 2011

Memoria (licenciado en ciencias jurídicas y sociales) / Autor no autoriza el acceso a texto completo de su documento / En el presente ensayo se realiza una exposición crítica de cinco aportes relacionados al concepto de libertad. Como texto base de la discusión moderna tal concepto, se analiza “Two Concepts of Liberty” de Isaiah Berlin. Se argumenta que la definición de libertad negativa de Berlin no atiende exclusivamente a la ausencia de interferencias, sino más bien a la existencia de un área de alternativas, y que la definición positiva, relacionada a la idea de “ser dueño de sí”, sólo cae en las consecuencias totalitarias que Berlin le atribuye producto de una diferencia en el nivel de análisis, mas no por la estructura propia del concepto. A continuación se revisan cuatro críticas a este texto. (1) “Negative and Positive Freedom”, de Gerald MacCallum, donde se presenta la tesis de un concepto unitario de libertad. Se argumentará que tal concepto sólo constituye una versión ampliada del concepto negativo de Berlin, no logrando incorporar el concepto positivo. (2) “A Third Concept of Liberty”, de Quentin Skinner, quien agrega a la discusión el concepto republicano de libertad. Se argumentará que para introducir tal concepto Skinner redujo el sentido del concepto positivo, no incorporando por tanto un concepto ajeno a los introducidos por Berlin. (3) “What’s Wrong with Negative Liberty”, de Charles Taylor, quien critica la libertad negativa Hobbesiano como un concepto insuficiente (crudo). Se argumenta que para llegar a las conclusiones que Taylor sostiene, no se requiere la introducción de la noción de autorrealización dentro del concepto negativo. (4) “Freedom as an Ideal”, de Raymond Geuss, quien junto con evidenciar la existencia de más conceptos de libertad, realiza la distinción de la libertad en sentidos interno y externo. En las conclusiones, esta distinción es tomada para sostener una clasificación de la libertad en seis variables (positiva, negativa; interna, externa; individual, colectiva). / 27/12/2019