The current study proposed a new model, termed the cross-classified multiple membership latent variable regression (CCMM-LVR) model, to be utilized for multiple membership data structures (for example, in the presence of student mobility across schools) that provides an extension to the three-level latent variable regression model (HM3-LVR). The HM3-LVR model is beneficial for testing more flexible, directional hypotheses about growth trajectory parameters and handles pure clustering of participants within higher-level units. However, the HM3-LVR model involves the assumption that students remain in the same cluster (school) throughout the duration of the time period of interest. The CCMM-LVR model, on the other hand, appropriately models the participants’ changing clusters over time. The first purpose of this study was to demonstrate use and interpretation of the CCMM-LVR model and its parameters with a large-scale longitudinal dataset that had a multiple membership data structure (i.e., student mobility). The impact of ignoring mobility in the real data was investigated by comparing parameter estimates, standard error estimates, and model fit indices for the two estimating models (CCMM-LVR and HM3-LVR). The second purpose of the dissertation was to conduct a simulation study to try to understand the source of potential differences between the two estimating models and find out which model’s estimates were closer to the truth given the conditions investigated. The manipulated conditions in the simulation study included the mobility rate, number of clustering units, number of individuals (i.e., students) per cluster (here, school), and number of measurement occasions per individual. The outcomes investigated in the simulation study included relative parameter bias, relative standard error bias, root mean square error, and coverage rates of the 95% credible intervals. Substantial bias was found across conditions for both models, but the CCMM-LVR model resulted in the least amount of relative parameter bias and more efficient estimates of the parameters, especially for larger numbers of clustering units. The results of the real data and simulation studies are discussed, along with the implications for applied researchers for when to consider using the CCMM-LVR model versus the misspecified HM3-LVR model. / text

Point source extraction is critical to proper analysis of images containing point sources obtained by focal plane array cameras. Two popular methods of extracting the intensity of a point source are aperture photometry and point spread function fitting. Digital aperture photometry encompasses procedures utilized to extract the intensity of an imaged point source. It has been used by astronomers in various forms for calculating stellar brightness. It is also useful for doing analysis of data associated with other unresolved radiating objects. The various aperture photometry methods include the two-aperture method, aperture correction, and growth curve method. The growth curve method utilizes integrated irradiance within an aperture versus growing aperture size. Signal to noise ratio, imperfect backgrounds, moving and off centered targets, and noise structure are just a few of the items that can cause problems with point source extraction. This thesis presents a study of how best to apply the growth curve method. Multiple synthetic image sets were produced to replicate real world data. The synthetic images contain a Gaussian target of known intensity. Noise was added to the images, and various image related parameters were altered. The growth curve method is then applied to each data set using every reasonable aperture size combination to calculate the target intensity. It will be shown that for different types of data, the most optimal application of the growth curve method can be determined. An algorithm is presented that can be applied to all data sets that fall within the scope of this study will be presented.

Point source extraction is critical to proper analysis of images containing point sources obtained by focal plane array cameras. Two popular methods of extracting the intensity of a point source are aperture photometry and point spread function fitting. Digital aperture photometry encompasses procedures utilized to extract the intensity of an imaged point source. It has been used by astronomers in various forms for calculating stellar brightness. It is also useful for doing analysis of data associated with other unresolved radiating objects. The various aperture photometry methods include the two-aperture method, aperture correction, and growth curve method.The growth curve method utilizes integrated irradiance within an aperture versus growing aperture size. Signal to noise ratio, imperfect backgrounds, moving and off centered targets, and noise structure are just a few of the items that can cause problems with point source extraction. This thesis presents a study of how best to apply the growth curve method.Multiple synthetic image sets were produced to replicate real world data. The synthetic images contain a Gaussian target of known intensity. Noise was added to the images, and various image related parameters were altered. The growth curve method is then applied to each data set using every reasonable aperture size combination to calculate the target intensity. It will be shown that for different types of data, the most optimal application of the growth curve method can be determined. An algorithm is presented that can be applied to all data sets that fall within the scope of this study will be presented.

This study examined science achievement growth across elementary and middle school and parent school involvement using the Early Childhood Longitudinal Study – Kindergarten Class of 1998 – 1999 (ECLS-K). The ECLS-K is a nationally representative kindergarten cohort of students from public and private schools who attended full-day or half-day kindergarten class in 1998 – 1999. The present study’s sample (N = 8,070) was based on students that had a sampling weight available from the public-use data file. Students were assessed in science achievement at third, fifth, and eighth grades and parents of the students were surveyed at the same time points. Analyses using latent growth curve modeling with time invariant and varying covariates in an SEM framework revealed a positive relationship between science achievement and parent involvement at eighth grade. Furthermore, there were gender and racial/ethnic differences in parents’ school involvement as a predictor of science achievement. Findings indicated that students with lower initial science achievement scores had a faster rate of growth across time. The achievement gap between low and high achievers in earth, space and life sciences lessened from elementary to middle school. Parents’ involvement with school usually tapers off after elementary school, but due to parent school involvement being a significant predictor of eighth grade science achievement, later school involvement may need to be supported and better implemented in secondary schooling.

The purpose of this study was to elucidate some of the physiological characteristics of V. stercoraria with regard to oxygen requirements, growth, nutritional requirements, pH effects on growth and growth factors.

Prior research demonstrates that military service disconnects men from past social and personal disadvantages and thus potentially alters normal life-course patterns of development. Much of this research, however, has been conducted only with World War II veterans. Relatively few studies have examined the influence of military service in Vietnam and its impact on altering individual trajectories of development. Through latent growth curve models, the authors examine the impact of military service in Vietnam on drug use and arrests across the life-course. Longitudinal data collected by the Marion County Youth study (1964-1979) were used to track a sample of men over a 15-year period. Analyses of these data revealed substantial nonrandom selection effects associated with service in Vietnam. Lower-class youths with already established delinquent patterns were significantly more likely to have served in Vietnam. It also appears, however, that service in Vietnam significantly increased individual drug use and, hence, offending rates.

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In the 21st century, the division of housework remains gendered, with women on average still spending more time doing chores than their male partners. While research has studied why this phenomenon is so persistent, few studies have yet been able to assess the effect of gender ideology and socio-economic resources at the same time, usually due to data restrictions. We use data from the pairfam, a new and innovative German panel study, in order to test the effect of absolute and relative resources as well as his and her gender ideology on the division of housework. We employ a life course perspective and analyze trajectories of couples' housework division over time, using multi-level random effects growth curve models. We find that an egalitarian gender ideology of both him and her significantly predicts more egalitarian division-trajectories, while neither absolute nor relative resources appear to have an effect on the division of housework over time. Furthermore, our results expand the literature by investigating how these processes differ among childless couples and couples who experience the first birth.

The aim of the thesis was to evaluate the feeding parameters of hybrid B.U.T. 6 at selected farm. Six batches of tom turkeys were evaluated in this study. The growth intensity analysis was performed based on weekly weighing. The average live weight was 21.83 kg at the age of 21 weeks. The highest value was in the 3rd batch (22.18 kg) and the lowest value was in the 2nd and the 6th batch (21.62 kg). In comparison with the "Management guide", the differences in average weight from the 5th week of age to the end of fattening were evaluated as statistically significant. The average feed conversion ratio was registered 2.73 kg. The highest feed conversion was in the 1st batch (2.82 kg) and the lowest was in the 5th batch (2.62 kg). The average inflection point was reached in the 14th week (12.1 kg). First the inflection point was achieved in the 1st and 2nd batch (13.6 weeks; 11.7 kg and 13.7 weeks; 11.4 kg) and at the latest in the 4th batch (15.5 weeks; 13.6 kg). The average maximum daily gain was reached 203.1 g (13.6 weeks). The highest was in the 3rd batch (204.9 g; 13.6 weeks) and the lowest was in the 4th batch (195.3 g; 14.3 weeks). The average mortality rate was found 6.39%. The highest mortality rate was in the 6th batch (8.44%; 858 pcs) and the lowest was in the 4th batch (4.50%; 457 pcs).

This study was undertaken to evaluate gender differences in predictors of substance use in clinic-referred, Hispanic American adolescents with substance use disorders. Individual (disruptive behavior disorders, depression) and family variables (family conflict, parental monitoring) were evaluated as predictors of the initial level and change over time in marijuana use, and gender was evaluated as a moderator of the associations. The study involved an analysis of an existing dataset of 113 Hispanic American adolescents (93 boys; age 12 to 17) referred for outpatient treatment for substance abuse and their parental guardian. Participants and parental guardians completed questionnaires and a structured interview to report on predictor variables at baseline and marijuana use at baseline and 3-, 6-, 12-, and 18-months post-baseline. Latent growth curve modeling was conducted to evaluate the study hypotheses. Adolescents reported high levels of marijuana use at baseline and relatively stable levels of marijuana use over time. Treatment and gender effects influenced the marijuana use trajectory. Girls exhibited more impaired psychosocial functioning than boys, including worse disruptive behavior problems and depression and lower levels of parental monitoring. Depression was negatively associated with marijuana use longitudinally. Overall, individual and family risk factors are associated with adolescent marijuana use in complex ways. Implications for intervention are discussed.