The demand for STEM college graduates is increasing. However, recent studies show there are not enough STEM majors to fulfill this need. This deficiency can be partially attributed to a gender discrepancy in the number of female STEM graduates and to the high rate of attrition of STEM majors. As STEM attrition has been associated with students being unprepared for STEM coursework, it is important to understand how STEM graduates change in achievement levels from middle school through high school and to have accurate readiness indicators for first-year STEM coursework. This study aimed to address these issues by comparing the achievement growth of STEM majors to non-STEM majors by gender in Science, Math, and Reading from Grade 6 to Grade 11 through latent growth models (LGMs). Then STEM Readiness Benchmarks were established in Science and Math on the Iowas (IAs) for typical first-year STEM courses and validity evidence was provided for the benchmarks. Results from the LGM analyses indicated that STEM graduates start at higher achievement levels in Grade 6 and maintain higher achievement levels through Grade 11 in all subjects. In addition, gender differences were examined. The findings indicate that students with high achievement levels self-select as STEM majors, regardless of gender. In addition, they suggest that students who are not on-track for a STEM degree may need to begin remediation prior to high school. Results from the benchmark analyses indicate that STEM coursework is more demanding and that students need to be better prepared academically in science and math if planning to pursue a STEM degree. In addition, the STEM Readiness Benchmarks were more accurate in predicting success in STEM courses than if general college readiness benchmarks were utilized. Also, students who met the STEM Readiness Benchmarks were more likely to graduate with a STEM degree. This study provides valuable information on STEM readiness to students, educators, and college admissions officers. Findings from this study can be used to better understand the level of academic achievement necessary to be successful as a STEM major and to provide guidance for students considering STEM majors in college. If students are being encouraged to purse STEM majors, it is important they have accurate information regarding their chances of success in STEM coursework.

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abstract: Researchers who conduct longitudinal studies are inherently interested in studying individual and population changes over time (e.g., mathematics achievement, subjective well-being). To answer such research questions, models of change (e.g., growth models) make the assumption of longitudinal measurement invariance. In many applied situations, key constructs are measured by a collection of ordered-categorical indicators (e.g., Likert scale items). To evaluate longitudinal measurement invariance with ordered-categorical indicators, a set of hierarchical models can be sequentially tested and compared. If the statistical tests of measurement invariance fail to be supported for one of the models, it is useful to have a method with which to gauge the practical significance of the differences in measurement model parameters over time. Drawing on studies of latent growth models and second-order latent growth models with continuous indicators (e.g., Kim & Willson, 2014a; 2014b; Leite, 2007; Wirth, 2008), this study examined the performance of a potential sensitivity analysis to gauge the practical significance of violations of longitudinal measurement invariance for ordered-categorical indicators using second-order latent growth models. The change in the estimate of the second-order growth parameters following the addition of an incorrect level of measurement invariance constraints at the first-order level was used as an effect size for measurement non-invariance. This study investigated how sensitive the proposed sensitivity analysis was to different locations of non-invariance (i.e., non-invariance in the factor loadings, the thresholds, and the unique factor variances) given a sufficient sample size. This study also examined whether the sensitivity of the proposed sensitivity analysis depended on a number of other factors including the magnitude of non-invariance, the number of non-invariant indicators, the number of non-invariant occasions, and the number of response categories in the indicators. / Dissertation/Thesis / Doctoral Dissertation Psychology 2016

The purpose of this research was to compare results from two approaches to measuring change over time. The multilevel model (MLM) and latent growth model (LGM) were imposed and the parameter estimates were compared, along with model fit. The study came out of education and used data collected from 191 teachers as part of a professional development intervention in science, which took place over four years. There were missing data as a result of teacher attrition. Teachers reported use of reform-oriented practices (ROP) was used as the outcome, and teacher-level variables were examined for their impact on initial ROP and change in ROP from baseline to one year after the intervention. Change in ROP was examined using a piecewise change model where two linear slopes were modeled. The first slope estimated the change from baseline to T1, or the initial change after the intervention while the second slope estimated the change from T1 to T3, or the secondary change. Parameter estimates obtained from MLM and LGM for a model using the error covariance structure commonly assumed in MLM (i.e., random slopes, homogeneous level-1 variance) were nearly identical. Models with various alternative covariance structures (commonly associated with the LGM framework) were examined, and results were nearly identical. Most of the model fit information was in agreement regarding the best fitting model being the model that assumed the typical MLM error covariance structure with the exception of the standardized root mean square residual (SRMR) fit index. The results from the models demonstrated that ROP increased after participating in the first year of the intervention and this level was sustained, though did not increase significantly in subsequent years. There was more variation in ROP at baseline. This information tells us that the intervention was successful in that after participating in the intervention the teachers' used ROP more frequently. The success of the intervention did not depend on any of the predictors that we assessed, and, as a group, the teachers became more similar in their use of reform-oriented practices over time.

本研究之目的是檢驗因應與創傷後成長隨時間變化的相互關聯性，除了重複驗證因應與創傷後成長的時序關係之外，考量創傷後成長不同向度之間可能具有不同特性，本研究也進一步探討不同向度的創傷後成長與不同因應向度之間的關係是否有所差異。創傷後成長方面，除了將創傷後成長視為單一構念之外，以Ho等人(2013)針對台灣女性乳癌樣本之因素分析結果為基礎，將創傷後成長初步分為個體內PTG與個體間PTG；因應向度方面，則根據探索性因素分析之結果將因應策略分為自我導向式因應、社會導向式因應和逃避因應等三個因應向度。 本研究採用縱貫研究法，針對中部某教學醫院之初診斷女性乳癌患者進行為期兩年的追蹤研究，分別在術後三個月(T1)、術後半年(T2)、術後一年(T3)以及術後兩年(T4)進行調查，測量參與者在癌症壓力之後所使用的因應策略及創傷後成長，最後完成四個時間點測量的研究參與者共283人。統計分析方法方面，因考量因應與創傷後成長會隨時間而變動的可能性，故採用適合縱貫資料且能估計變項發展軌跡的潛在成長模式 (Latent growth model) 來進行資料分析。 研究結果顯示不同向度的因應與不同向度的創傷後成長之間關聯性不同，但此差異是反映在不同因應向度之間，至於相同因應與不同向度PTG之間的結果則無太大差異：在測量初始點，不管是哪一種因應方式，都跟整體PTG、不同向度PTG具有交互預測的關係，但在斜率方面，只有自我導向因應與整體PTG以及不同向度的PTG具有相互預測性。但是否區分個體內PTG和個體間PTG，對於因應與創傷後成長之關聯性結果差異不大。過去對於PTG是單一構念或多因素的爭論方興未艾，後續討論也納入是否有必要區分創傷後成長不同向度的必要性，最後討論本研究之限制，並提供未來研究可供參考之方向。 / Aims: The purpose of this article was to examine the time-varying reciprocal relationships between coping and posttraumatic growth (PTG) as well as their domains. PTG was divided into two dimensions－intrapersonal PTG (intra-PTG) and interpersonal PTG (inter-PTG) as suggested in Ho et al. (2013) while coping was divided into self-sufficient coping, socially-supported coping, and avoidant copingbased on the results of our exploratory factor analysis (EFA). Methods: Participants were Taiwanese women underwent surgery for breast cancer. Measures of PTG and coping were assessed at three-month, six-month, one-year and two-year. Of the 358 women who were recruited, 283 completed all four measures and were included in the analyses. As coping and PTG may change over time, the data was analyzed using latent growth curve model (LGM). Results: Our results showed that there’re different relationships between coping strategies and PTG dimensions. At the initial measure, all kinds of coping strategies have a reciprocal relationship with PTGs, but when it comes to the directions between slopes of coping and PTG, only self-sufficient coping has a reciprocal relationship with PTG. There’s almost no difference while comparing different PTG dimensions models. In other words, there’s almost no difference in LGM models between intra-PTG and inter-PTG. In the end of the study, the necessity of the division of PTG and limitations of this study were discussed.

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Background. DNA methylation (DNAm) is a removable chemical modification to the DNA sequence intimately associated with genomic stability, cellular identity, and gene expression. DNAm patterning reflects joint contributions from genetic, environmental, and behavioral factors. As such, differences in DNAm patterns may explain interindividual variability in risk liability for complex traits like major depression (MD). Hundreds of significant DNAm loci have been identified using cross-sectional association studies. This dissertation builds on that foundational work to explore novel statistical approaches for longitudinal DNAm analyses. Methods. Repeated measures of genome-wide DNAm and social and environmental determinants of health were collected up to six times across pregnancy and the first year postpartum as part of the Pregnancy, Race, Environment, Genes (PREG) Study. Statistical analyses were completed using a combination of the R statistical environment, Bioconductor packages, MplusAutomate, and Mplus software. Prenatal maternal DNAm was measured using the Infinium HumanMethylation450 Beadchip. Latent growth curve models were used to analyze repeated measures of maternal DNAm and to quantify site-level DNAm latent trajectories over the course of pregnancy. The purpose was to characterize the location and nature of prenatal DNAm changes and to test the influence of clinical and demographic factors on prenatal DNAm remodeling. Results. Over 1300 sites had DNAm trajectories significantly associated with either maternal age or lifetime MD. Many of the genomic regions overlapping significant results replicated previous age and MD-related genetic and DNAm findings. Discussion. Future work should capitalize on the progress made here integrating structural equation modeling (SEM) with longitudinal omics-level measures.

本研究主要目的是以文獻分析、問卷調查、潛在成長模式等方法探討數學焦慮、數學學習動機與數學學業成就等三個變項的縱貫模式及因果結構模式。根據五百二十九位國三學生所填的五波調查問卷資料，進行兩部分研究。 研究一乃在估算數學焦慮、數學學習動機、數學學業成就的潛在改變量模式及 數學焦慮、數學學習動機、數學學業成就兩兩之間的因果結構模式。結果發現1.數學焦慮縱貫模式上，符合「焦慮遞增理論」；2.數學學習動機縱貫模式上，符合「動機先升後降理論」；3.數學學業成就縱貫模式上，符合「成就先升後降理論」； 4.數學焦慮與數學學習動機因果結構模式上，符合「動機焦慮交互激發效果理論」；5.數學焦慮與數學學業成就因果結構模式上，符合「焦慮成就交互抑制效果理論」；6.數學學習動機與數學學業成就因果結構模式上，符合「動機成就交互激發效果理論」。 研究二則依據研究一二變項因果結構統計驗證成立的三套理論，建構出三變項因果結構六模式，並驗證有無中介效果。結果顯示，1.前焦慮、中動機、後學業成就因果模式上，符合「動機未完全中介前焦慮、後學業成就理論」；2. 前動機、中焦慮、後學業成就因果模式上，符合「焦慮未完全中介前動機、後學業成就理論」；3.前焦慮、中學業成就、後動機因果模式上，符合「學業成就未完全中介前焦慮、後動機理論」；4.前學業成就、中焦慮、後動機因果模式上，符合「焦慮未完全中介前學業成就、後動機理論」；5. 前動機、中學業成就、後焦慮因果模式上，符合「學業成就未完全中介前動機、後焦慮理論」；6.前學業成就、中動機、後焦慮因果模式上，符合「動機未完全中介前學業成就、後焦慮理論」。 除了上述結果外，研究也對數學焦慮、數學學習動機與數學學業成就縱貫模式的趨勢與時間效果量，國三學生轉折點界定，數學焦慮、數學學習動機與數學學業成就適當模式產出及個別中介角色剖析有深入探討。 / This study, using literature review, questionnaire survey, and latent growth model, investigated the longitudinal model and causal model among math anxiety, learning motivation, and academic achievement. After collecting 529 students with 5 waves, I conducted two studies. The purpose of study 1 was to estimate the latent change model and the causal model of math anxiety, learning motivation, and academic achievement. Results showed that 1. The anxiety increasing theory was supported by the math anxiety longitudinal model. 2. The first increasing then decreasing theory was supported by the math learning motivation longitudinal model. 3. The first increasing then decreasing theory was supported by the math academic achievement longitudinal model. 4. The reciprocal activated effect theory was supported by the math anxiety and learning motivation causal models. 5. The reciprocal inhibitive effect theory was supported by the math anxiety and academic achievement causal models. 6. The reciprocal activated effect theory was supported by the math learning motivation and academic achievement causal models. According to the final three theories stated above and proved by study 1, I constructed the six causal models in order to verify the mediated effects of math anxiety, math learning motivation, and math academic achievement. I found that 1. Math learning motivation did not mediate fully the effects on early math anxiety and late math academic achievement. 2. Math anxiety did not mediate fully the effects on early math learning motivation and late math academic achievement. 3. Math academic achievement did not mediate fully the effects on early math anxiety and late math learning motivation. 4. Math anxiety did not mediate fully the effects on early math academic achievement and late math learning motivation. 5. Math academic achievement did not mediate fully the effects on early math learning motivation math and late math anxiety. 6. Math learning motivation did not mediate fully the effects on early math academic achievement and late math anxiety. In addition, the research also explored the longitudinal model trend and effect, the key period for 3rd year junior high school students, the proper models, and the mediated roles among math anxiety, learning motivation, and academic achievement.