Browsing by Subject "Longitudinal data"

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    Bayesian Modeling of Associations in Bivariate Mixed-Effects Models for Segmented Growth Curves
    (2018-11) Peralta Torres, Yadira
    Developmental processes rarely occur in isolation; often the growth curves of two or more variables are interdependent. In addition, frequently, growth curves do not portray a constant pattern of change. Different stages or segments of development are present in the data. Bivariate piecewise linear mixed-effects models (BPLMEM) are a useful statistical framework to simultaneously describe two processes that portray segmented linear trajectories and to investigate their associations over time. Interrelations between the growth curves are measured by assuming a joint distribution of the random-effects parameters of each outcome variable. Furthermore, associations in the outcome variables collected from the same subject should be taken into account when they are modeled jointly. This association is modeled by correlating the error variance parameters of each outcome variable. There are several drawbacks in the literature of bivariate piecewise mixed-effects models. An important limitation in the BPLMEMs literature is that researchers have assumed uncorrelated residual errors across the two longitudinal processes, which is something unlikely to hold in practice. Also, current modeling choices for the random-effects in bivariate piecewise mixed-effects model have shortcomings. For instance, researchers have unintentionally imposed dependencies among the elements of the covariance matrix associated with the random-effects; or they have modeled only few of its covariance parameters determined by the research interest. In addition, simulation studies using BPLMEMs are scarce. Little is known about the performance of bivariate piecewise mixed-effects models under different correlational scenarios of the random-effects parameters and the error variances. Furthermore, a criticism to the piecewise linear model is a hypothesized abrupt change between one linear segment to another because this performance may not be true for all empirical scenarios. However, although a smooth transition or adaptation period between linear segments might be more realistic, the piecewise linear model is extensively used in practice. Thus, it is natural to wonder under which scenarios this is an acceptable choice. The purpose of the present study was to develop a BPLMEM using a Bayesian inference approach allowing the estimation of the association between error variances and providing a more robust modeling choice for the random-effects. Furthermore, the performance of the BPLMEM was investigated via a Monte Carlo simulation study focusing on the strength of the associations of the error variance parameters and the growth curves (represented by the random-effects’ correlational structure). An additional purpose was to empirically characterize scenarios for which the piecewise linear model gives a reasonable approximation to an underlying smoothed segmented trajectory given by a quadratic bend joining the linear phases of growth. Lastly, the contribution of bivariate mixed-effects modeling approaches is illustrated by using a BPLMEM to investigate the joint development of mathematics and reading achievement and the association between their longitudinal trajectories. This constitutes a novel approach to examine associations between educational domains over time. Simulation results showed that the strength of the association between the growth curves and the sample size had a significant effect on the performance of the BPLMEM. Specifically, lower relative bias of parameter estimates and higher model convergence was related to a stronger correlational structure between the random-effects of the growth curves. Likewise, slightly higher coverage rates and better convergence were associated with a smaller sample size. In addition, it was possible to identify cases for which the piecewise linear model had an acceptable performance when the true underlying trajectory had an adaptation period or bend between linear segments. Scenarios with small or centered bends were accurately described by a piecewise linear model. Results from the illustrative example suggested that mathematics and reading achievement are positively associated all along their segmented trajectories and that the strength of such association decreases over time. In addition, evidence of the same patterns of association of reading over mathematics and mathematics over reading were found.
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    Longitudinal intergroup contact model comparison at the multicultural High School United World College Red Cross Nordic
    (2014-09) Gabrielsen, Eva Susanne Brogger
    The United World College Red Cross Nordic (RCN) is a unique high school: 200 students representing roughly ninety countries pursue the two-year International Baccalaureate degree in an environment characterized by diversity, multicultural learning, intergroup cooperation, and peace education. The boarding school’s mission is to “make education a force to unite people, nations and cultures for peace and a sustainable future,” but to date, no formal assessments have evaluated the effectiveness of the multicultural peace education program on students’ decreased outgroup bias and prejudice. This longitudinal field study sought to evaluate RCN’s multicultural peace education program by assessing changes in students’ intergroup bias: negative outgroup emotions, desire for social distance, and generalized ethnocentrism.Three established social-psychological models of intergroup contact, the contact hypothesis, the intergroup contact model, and the common ingroup identity model, were compared and contrasted with data-driven linear mixed-effects built on the models’ contact conditions to determine whether a theoretical or data-driven model was the best fit for the current sample. The contact hypothesis specifies five contact conditions: equal status, common goals, intergroup cooperation, institutional support, and acquaintance potential. The intergroup contact model uses the five contact hypothesis conditions as a foundation, and adds that intergroup salience is important in intergroup contact situations. The common ingroup identity model specifies a common ingroup identified with by all participants in intergroup contact as the facilitator for success.A balanced panel design was established to survey students four times over their two years at RCN: within the first week of the first year, within the last week of the first year, within the first week of the second year, and within the last week of the second year. 272 students representing 96 countries participated in at least one of the four survey collections. Twenty-eight students, representing either peaceful or conflicted countries, were interviewed at the beginning and at the end of their RCN education. The third, and cross-sectional, sample upon which the analyses herein rest was of 256 United World College alumni, representing 77 countries and ten UWCs.By Time 4, students reported spending less time each week on their extra-academic commitments, but reported no change in the hours spent with friends. Perceptions of the presence of facilitating contact conditions and students’ self-reported intergroup anxiety decreased from Time 1 to Time 2, increased from Time 2 to Time 3, and decreased again from Time 3 to Time 4, the total change over time was significant.Students reported non-significant decreases in negative outgroup emotions, desire for social distance, and generalized ethnocentrism. Data-driven intergroup contact models were the consistent best fit for the data, for all three measures of intergroup bias. The particular covariates differed for the three: for negative outgroup emotions the covariates included equal status, common goals, and intergroup salience; for need for social distance the covariates included equal status, intergroup cooperation, and intergroup salience; for generalized ethnocentrism the covariates included intergroup cooperation and intergroup salience. For negative outgroup emotions and desire for social distance, adding intergroup salience as a predictor to the common ingroup identity model’s LME improves the models’ fit above and beyond all the best-fitting models. Cross-sectional alumni data corroborated findings from the longitudinal data on current students. The 256 alumni surveyed differed significantly from Time 4 students on almost all measures. Alumni reported significantly higher levels of religiosity, liberal political orientation, trust, empathy, and the eight contact conditions, and significantly lower levels of generalized ethnocentrism, intergroup anxiety, closedmindedness and social dominance orientation. Older alumni did not significantly differ from younger alumni, but men differed from women. Because of the cross-sectional nature of the data, LME models were inappropriate and linear regressions were used to establish whether the best-fitting LME models held in the alumni sample; they did not.Content analyses of 25 complete pre- and post-interviews showed different trends for the students from conflicted countries compared to students from peaceful countries. Themes that arose include increased knowledge of conflicts around the world, critical thinking and awareness of own self, ability and willingness to trust and show empathy toward others, conflict management skills, and finally, growth. Additionally, themes that emerged spontaneously across the interviews included consistency in thinking and an increased importance assigned values such as health, happiness, and freedom. Using the Linguistic Inquiry Word Count software, the following were found to differ significantly between Time 1 and Time 4: English proficiency, talking about family, the use of negative emotion words, talking about feelings, and insight.Several suggestions are presented to explain the lack of changes in intergroup bias. Because intergroup salience was found to be one of the most significant contact conditions, recommendations are provided for how RCN can continue to capitalize on representativeness among its students. The importance of RCN identity, too, is explored. Because pure contact is not enough, RCN must continue its work of facilitating contact conditions to encourage and increase the instances of successful intergroup contact.
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    Mixed effects models for size-attained data.
    (2012-01) Lendway, Lisa M.
    It is rare to have longitudinal data on the somatic growth of fish, that is, how their body length changes over time. In most temperate fish, scales or other hard parts, like otoliths or other bones, form annual rings or increments. Growth of the hard part can be measured, thereby giving a longitudinal record of hard part growth from cross-sectional data. Methods such as back-calculation and linear mixed-effects models have used the growth of hard parts to infer somatic growth. At times, it is not feasible to obtain the measurements of the hard part. Body length at time of capture is much easier to measure and reflects somatic growth, which is usually of more interest. In this thesis, I present a model that is based on a longitudinal approach but models length at time of capture, rather than the yearly body growth. It also allows for estimation of environmental impact on growth.
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    Panel conditioning in longitudinal social science surveys
    (2013-07) Halpern-Manners, Andrew
    Researchers who utilize data from longitudinal surveys nearly always assume that respondents' attributes are not changed as a result of being measured. Yet research in cognitive psychology, political science, and elsewhere suggests that the experience of being interviewed can spark important changes in the way respondents behave, in the attitudes that they possess, and in their willingness or ability to answer questions accurately when they are re-interviewed in subsequent waves. In this dissertation, I evaluate the severity of this problem in longitudinal social science surveys. Using a combination of observational and experimental data, I show that "panel conditioning" has the potential to affect a wide range of attitudinal and behavioral measures, including many items that are commonly used in sociological and demographic research. The causal mechanisms that give rise to these effects are discussed and a large-scale follow-up project is proposed.