Classification of data from repeated measurements is useful in various disciplines, for example that of medicine. This thesis explores how classification trees (CART) can be used for classifying repeated measures data. The reader is introduced to variations of the CART algorithm which can be used for classifying the data set and tests the performance of these algorithms on a data set that can be modelled using bilinear regression. The performance is compared with that of a classification rule based on linear discriminant analysis. It is found that while the performance of the CART algorithm can be satisfactory, using linear discriminant analysis is more reliable for achieving good results. / Klassificering av data från upprepade mätningar är användbart inom olika discipliner, till exempel medicin. Denna uppsats undersöker hur klassificeringsträd (CART) kan användas för att klassificera upprepade mätningar. Läsaren introduceras till varianter av CART-algoritmen som kan användas för att klassificera datamängden och testar prestandan för dessa algoritmer på en datamängd som kan modelleras med hjälp av bilinjär regression. Prestandan jämförs med en klassificeringsregel baserad på linjär diskriminantanalys. Det har visar sig att även om prestandan för CART-algoritmen kan vara tillfredsställande, är användning av linjär diskriminantanalys mer tillförlitlig för att uppnå goda resultat.

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<p>Recent advances in technology have allowed researchers to collect high-dimensional biological data simultaneously. In genomic studies, for instance, measurements from tens of thousands of genes are taken from individuals across several experimental groups. In time course microarray experiments, gene expression is measured at several time points for each individual across the whole genome resulting in massive amount of data. In such experiments, researchers are faced with two types of high-dimensionality. The first is global high-dimensionality, which is common to all genomic experiments. The global high-dimensionality arises because inference is being done on tens of thousands of genes resulting in multiplicity. This challenge is often dealt with statistical methods for multiple comparison, such as the Bonferroni correction or false discovery rate (FDR). We refer to the second type of high-dimensionality as gene specific high-dimensionality, which arises in time course microarry experiments due to the fact that, in such experiments, sample size is often smaller than the number of time points ($n</p> <p>In this thesis, we use the growth curve model (GCM), which is a generalized multivariate analysis of variance (GMANOVA) model, and propose a moderated test statistic for testing a special case of the general linear hypothesis, which is specially useful for identifying genes that are expressed. We use the trace test for the GCM and modify it so that it can be used in high-dimensional situations. We consider two types of moderation: the Moore-Penrose generalized inverse and Stein's shrinkage estimator of $ S $. We performed extensive simulations to show performance of the moderated test, and compared the results with original trace test. We calculated empirical level and power of the test under many scenarios. Although the focus is on hypothesis testing, we also provided moderated maximum likelihood estimator for the parameter matrix and assessed its performance by investigating bias and mean squared error of the estimator and compared the results with those of the maximum likelihood estimators. Since the parameters are matrices, we consider distance measures in both power and level comparisons as well as when investigating bias and mean squared error. We also illustrated our approach using time course microarray data taken from a study on Lung Cancer. We were able to filter out 1053 genes as non-noise genes from a pool of 22,277 genes which is approximately 5\% of the total number of genes. This is in sync with results from most biological experiments where around 5\% genes are found to be differentially expressed.</p> / Master of Science (MSc)

<p><strong>Background:</strong> Postnatal growth of preterm infants does not match recommended intrauterine growth, due to the initial weight loss that accompanies healthy body composition rearrangements after birth. Thus, optimal postnatal growth for preterm infants is currently unknown.</p> <p><strong>Objectives: </strong>(1)<strong> </strong>Collect longitudinal postnatal growth data of 30–36 week GA preterm infants with unimpaired postnatal adaptation; (2) Develop regressions that predict the growth trajectory such an infant will adjust to by days of life 7/14/21; (3) Extrapolate and validate the regressions downwards to 25 weeks.</p> <p><strong>Methods:</strong> Infants of 30–36 week GA, born/admitted to 1/5 participating centres between 2008–2012, who met pre-specified criteria for unimpaired postnatal adaptation and who had at minimum 14 days of data were included. Day-specific anthropometric data from birth to discharge were abstracted retrospectively. Z-score regressions for days 7/14/21 were developed. Regressions were then extrapolated to 25 weeks and validated using an independent study population.</p> <p><strong>Results:</strong> Of 6203 infants, 665 met the screening criteria. By day 14, infants adjusted to stable growth trajectories that were 84±13% of the recommended weight-for-age. Using the following predictors: GA, z-score at birth and hospital-centre, regressions accurately predicted z-scores at days 7, 14 (n=665; R²=0.939, 0.889) and 21 (n=333; R²=0.841). Validation using 25-29 week GA infants (n=173) suggested models were also accurate within this age-range.</p> <p><strong>Conclusion: </strong>These results provide robust estimates of a hypothesis of healthy postnatal growth for preterm infants. Future steps include assessing long-term outcomes in a randomized control trial and assessing the quality of growth using body composition analyses.</p> / Master of Science in Medical Sciences (MSMS)

<p><strong>Background:</strong> Developmental neuroscience research suggests that relative differences in emerging social skills between very young children with ASD may influence the trajectories of multiple important developmental domains, such as language ability. Such “cascade” associations between developmental trajectories may contribute in important ways to the substantial heterogeneity in symptoms and functioning seen in children with ASD. However, longitudinal research has yet to test such “cascade” models of change in children diagnosed with ASD.</p> <p><strong>Objectives:</strong> In this dissertation I aimed to model cascade patterns of association between social competence and language ability pathways in the year after diagnosis of ASD in preschool-aged children. Data for 365 participants aged 2-4 years old who had been recently diagnosed with ASD and followed prospectively were obtained from the “Pathways To Better Outcomes in ASD Study”.</p> <p><strong>Methods:</strong> Study 1 aimed to determine whether social competence and structural language ability could be measured as distinct constructs that were invariant over time and between clinically relevant groups of young children with ASD. Study 2 modeled longitudinal reciprocal associations between these domains. Study 3 addressed the issue of variability and change within this sample, and tested whether baseline levels and rate of change in one domain were associated with subsequent growth in the other.</p> <p><strong>Results:</strong> Social competence and language ability constructs were measurably distinct and invariant in a young sample comprising verbal and non-verbal children with ASD. Only small reciprocal cascade effects were evident between social and language pathways. Levels of social competence at time of diagnosis were significantly associated with subsequent language growth.</p> <p><strong>Conclusions:</strong> In preschoolers with ASD, advantages in social competence as measured at time of diagnosis appear to “spill over” in a feed-forward cascade model to influence progress in language ability. Social competence and language ability then appear to develop along more specialized, less interrelated pathways.</p> / Doctor of Philosophy (PhD)

Although the research literature supports the notion of language growth trajectories, primarily in monolingual English children, the shape and direction of English-language learners' (ELLs) language growth trajectories are largely unknown. The present study examined the shape of ELLs' language growth trajectories by estimating the initial status and the growth rates of specific oral language skills (mean length of utterance in words (MLUw), number of different words (NDW), and words per minute (WPM)) in each language during the first 3 years of formal schooling. This study was framed from the perspective of language as a dynamic system, composed of linguistic subsystems that change over time. This study utilized secondary data from a larger project, the Bilingual Language Literacy Project (BLLP), which collected narrative retell language samples produced in Spanish and English from ELL children. The final longitudinal dataset used in this study consisted of 12,248 oral narrative language samples (6,516 Spanish; 5,732 English) that were produced by 1,723 ELLs. This study examined the effect of three predictors on language growth: academic semester (metric of time), gender, and schooling. Growth curve model (GCM) testing was used to profile the longitudinal growth of the ELLs' oral language skills in Spanish and English over time. This study had a number of important findings regarding change over time, intra- and inter-individual variability, and the impact of initial status on growth. With regard to change over time: MLUw, NDW, and WPM demonstrated growth over time in Spanish and English; the shapes of Spanish (curvilinear, non-monotonic, and continuous) and English growth (linear, non-monotonic, and discontinuous) were similar within-language; language growth in Spanish was predicted by academic semester and gender; and language growth in English was predicted by academic semester, gender, and schooling. With regard to intra- and inter-individual variability: significant intra-individual differences in the growth of all the oral language measures, across each wave of measurement, were found for both languages; significant intra-individual differences in the initial status of participants for all the oral language measures were found for both languages; significant inter-individual differences in the growth rates were found for WPM-Spanish; and significant inter-individual differences in the growth rates were found for all the oral language measures in English. With regard to the impact of initial status on growth: the growth of MLUw-Spanish was systematically related to initial status (lower performers at initial status may not catch up to higher performers); the growth of NDW- and WPM-Spanish were unrelated to its initial status (lower performers at initial status may, or may not catch up to higher performers); and the growth of MLUw-, NDW-, and WPM-English was systematically related to initial status (lower performers at initial status may catch up to higher performers). With regard to the co-development of interconnected subsystems, qualitative observations (non-empirically tested) based on visual inspection and GCM estimates provided initial insight into the possible co-development occurring within- and across-languages. The present study broke new ground by specifying the shape of growth for MLUw, NDW, and WPM in the Spanish and English of ELLs during their first 3 years of formal schooling. The study had a number of methodological limitations that will guide and motivate future work on the language growth of ELLs. / Communication Sciences

Background: While drinking alcohol, one must choose between the immediate rewarding effects and the delayed reward of a healthier lifestyle. Individuals differ in their devaluation of a delayed reward based on the time required to receive it, i.e., delay discounting (DD). Previous studies have shown that adolescents discount more steeply than adults and that steeper DD is associated with heavier alcohol use in both groups. - Methods: In a large-scale longitudinal study, we investigated whether higher rates of DD are an antecedent or a consequence of alcohol use during adolescent development. As part of the IMAGEN project, 2220 adolescents completed the Monetary Choice Questionnaire as a DD measure, the Alcohol Use Disorders Identification Test, and the Timeline Follow Back interview at ages 14, 16, 18, and 22. Bivariate latent growth curve models were applied to investigate the relationship between DD and drinking. To explore the consequences of drinking, we computed the cumulative alcohol consumption and correlated it with the development of discounting. A subsample of 221 participants completed an intertemporal choice task (iTeCh) during functional magnetic resonance imaging at ages 14, 16, and 18. Repeated-measures ANOVA was used to differentiate between high-risk and low-risk drinkers on the development of neural processing during intertemporal choices. - Results: Overall, high rates of DD at age 14 predicted a greater increase in drinking over 8 years. In contrast, on average, moderate alcohol use did not affect DD from ages 14 to 22. Of note, we found indicators for less brain activity in top-down control areas during intertemporal choices in the participants who drank more. - Conclusions: Steep DD was shown to be a predictor rather than a consequence of alcohol use in low-level drinking adolescents. Important considerations for future longitudinal studies are the sampling strategies to be used and the reliability of the assessments.

This study compared 3 approaches for handling a fourth level of nesting structure when analyzing data from a cluster-randomized trial (CRT). CRTs can include 3 levels of nesting: repeated measures, individual, and cluster levels. However, above the cluster level, there may sometimes be an additional potentially important fourth level of nesting (e.g., schools, districts, etc., depending on the design) that is typically ignored in CRT data analysis. The current study examined the impact of ignoring this fourth level, accounting for it using a model-based approach, and accounting it using a design-based approach on parameter and standard error (SE) estimates. Several fixed effect and random effect variance parameters and SEs were biased across all 3 models. In the 4-level model, most SE biases decreased as the number of level 3 clusters increased and as the number of level 4 clusters decreased. Also, random effect variance biases decreased as the number of level 3 clusters increased. In the 3-level and complex models, SEs became more biased as the weight level 4 carried increased (i.e., larger intraclass correlation, more clusters at that level). The current results suggest that if a meaningful fourth level of nesting exists, future researchers should account for it using design-based approach; the model-based approach is not recommended. If the fourth level is not practically important, researchers may ignore it altogether.

The need for the identification and appropriate development of talent in organisations has led to a renewed interest in the accuracy of tools used in this context. The objectives of the study were to: (1) determine whether there is a significant difference in the growth in theoretical capability as predicted by Career Path Appreciation (CPA) 1 and CPA 2 among the sample population, (2) determine whether there is a significant difference in Mode as predicted by CPA 1 and CPA 2 among the sample population, and (3) formulate recommendations for Talent Management and Industrial and Organisational Psychology practices and future research. The CPA is a tool used for the selection and development of talent nationally and internationally. Limited recent test-retest research has been done regarding the utilisation of the CPA in this context. Scholars in the field of industrial psychology could therefore benefit from follow-up research regarding the validity and reliability of the CPA. The research design is an ex post facto correlational design using longitudinal data of a sample of convenience (N=527). Overall, the results indicated a significant correlation between CLC for CPA 1 and CPA 2 as well as between Mode for CPA 1 and CPA 2. The CPA as a measure of theoretical capability is consistently accurate between measures and can be used with confidence for the identification and development of talent within organisations. / Industrial & Organisational Psychology / M. Admin. (Industrial and Organisational Psychology)

本研究採用一項有關青少年成長與發展調適問題的長期貫時性追蹤資料(1996-1999)，試圖突破過去討論青少年憂鬱症狀發展時，所用之横斷式資料的囿限，嘗試應用潛在成長曲線模型(Latent growth curve model, LGC Model)的分析方法，加入歷史時間的縱深，捕捉青少年憂鬱症狀的「起始狀態」、與「個別的成長軌跡發展」。以不扭曲地將所有受試青少年在三年間的內化症狀變化情形，忠實地描述出來。而後，加入「改變」因素的討論，企圖尋找能影響青少年憂鬱症狀發展軌跡的關鍵機制。 此研究主要目的即在「具象化」復原力的理論觀點，企圖加入動態的時間面向，確認負向生活事件與青少年憂鬱症狀發展軌跡之間的因果關聯，並探討來自個人、與環境脈絡中的關係運作，對青少年憂鬱症狀平均數、變化方向與速率的跨時間影響。研究結果明確回答：為什麼有些青少年在受到憂鬱症狀的負向影響之後，尚能有回復機會並「表現地比預期好」的疑問。至於針對一群憂鬱症狀發展呈現改善、或惡化的少數青少年樣本，在性別、自尊、負向生活事件、家庭親子互動、學校好朋友關係等特性上的差異，本研究亦逐一說明。 在理論層次上，本項研究結合適切的研究方法，從「靜態」到「動態」地觀察青少年的身心發展、自「個人」到「家庭系統內外」討論內外在資源對青少年復原的短暫以及長久影響效果，並以一般青少年為研究對象的作法，擴增了復原力理論的推論範疇與解釋深廣。研究顯示，青少年的「改善」或「惡化」憂鬱症狀發展軌跡，確實在環境脈絡的節制之下，存在著個別差異。此外，青少年起始的憂鬱狀態並不影響憂鬱症狀軌跡發展的變化率。家庭經濟不利這項負向生活事件，對於青少年憂鬱症狀的預測，只呈現短暫的初始影響。自尊和好朋友關係皆是青少年可以主動建構與可為之舉，為兩個最重要能影響青少年憂鬱症狀變化的關鍵因素。至於學校脈絡，則可視為在家庭脈絡之外，能提供青少年憂鬱症狀改變效果的新路徑，以及讓青少年可以順利「轉大人」之雙重機會的結構因素。 / Using data derived from a panel study (1996-1999) of long-term Taiwanese adolescent development and adaptation, this study intended to break through the limitations of cross-sectional studies, which plagued past studies of adolescents’ developing depressive symptoms. By employing the Latent Growth Curve Model (LGC Model), this study mainly attempted to feature the individual initial status and the trajectory of every adolescent’s developmental depressive symptoms, which concerned about the important functions of the dynamic historical time and space on youth internalizing symptoms, for the research purpose to reflect the real resilient outcome each adolescent displayed. Besides, in order to understand the key factors that were taken as positive and effective mechanisms to influence the initial status and rates of changes on youth trajectories of depressive symptoms, several latent constructs such as self-esteem and protective factors developed from family and school contexts were taken into accounts. Further, specified characteristics were noted to highlight the basic differences gradually showed between resilient improved adolescents and worsen ones. A positive-psychological stance was taken as the leading research perspective in this study. The results shows that familial economic hardship only affects the initial status of adolescent depressive symptoms, implying that this negative event just had a short-term effect on youth’s psychological well beings. Those who were initially vulnerable to familial negative event had opportunity to become resilient over time. As to the protective factors, self-esteem and cohesive good-friendship were two crucial facets adolescents could actively construct and make efforts for further resilient performances to be better than expected. The analyzing results indicated, interestingly, that parent-child relationship early obtained in family context and adolescent’s satisfaction with parenting merely counted for the initial impact on adolescent trajectories of depressive symptoms. Concerns and cohesive relationships acquired in school contexts, especially in classes, provided dual chances for adolescents to become resilient in a long run.