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Pathway is a set of genes which are predefined and serve a particular celluar or physiological function. Ranking pathways relevant to a particular phenotype can help researchers focus on a few sets of genes in pathways. In this thesis, a Bayesian hierarchical latent model was proposed using generalized linear random effects model. The advantage of the approach was that it can easily incorporate prior knowledges when the sample size was small and the number of genes was large. For the covariance matrix of a set of random variables, two Gaussian random processes were considered to construct the dependencies among genes in a pathway. One was based on the polynomial kernel and the other was based on the Gaussian kernel. Then these two kernels were compared with constant covariance matrix of the random effect by using the ratio, which was based on the joint posterior distribution with respect to each model. For mixture models, log-likelihood values were computed at different values of the mixture proportion, compared among mixtures of selected kernels and point-mass density (or constant covariance matrix). The approach was applied to a data set (Mootha et al., 2003) containing the expression profiles of type II diabetes where the motivation was to identify pathways that can discriminate between normal patients and patients with type II diabetes. / Master of Science

La presente tesi raggruppa tre contributi che analizzano la partecipazione dei minori ad attività lavorative e scolastiche in Marocco, le variabili correlate con il benessere individuale e le differenze nei livelli salariali in Albania. I tre saggi tentano di fornire analisi empiriche basate sulla letteratura più recente e di contribuire allo sviluppo della metodologia quantitativa più comunemente utilizzata. / The present thesis is a collection of three contributions which investigate children’s schooling and labour participation in Morocco, the correlates of subjective well being and the differences in wage levels in Albania. The papers try to carry out empirical analyses of these issues based on the most recent developments in the relevant literature and to contribute to the empirical methodology commonly used.

Food safety problems have gained national attention, and food recall is one of the most important indications of this concern. Third-party certifications have become a popular way to improve the safety and quality of products for consumers. Publications related to third-party certification usually focus on the motives and benefits of a particular certification. However, to date, no existing research investigates the effects of food recalls on certification adoption. This study uses Probit models with a binary endogenous explanatory variable to examine the relationship between food recalls and third-party certification, based on recalls occurring between January 1, 2015 and February 18, 2016. Marginal effects are used to interpret the impact of recalls and companies’ annual net sales on third-party certification adoption. Results reveal that past recalls significantly affect a firm’s likelihood of certification adoption.

Farmers generally produce multiple crops while selectively adopting modern technologies to meet various needs. The main aim of this study is, therefore, to identify the range of socio-economic factors influencing the adoption of modern agricultural technology in multiple food crops and the corresponding impacts on productivity and food availability at the farm-level in South-eastern Nigeria. In this study, three major food crops (i.e., rice, yam and cassava) and two elements of modern technologies (i.e., HYV seeds and inorganic fertilizers) are considered. The hypotheses of the study are that inverse farm size – technology adoption, size – productivity, size- profitability and size – food availability relationships exist in Nigerian agriculture. The research is based on an in-depth farm-survey of 400 farmers from two states (251 from Ebonyi and 149 from Anambra states) of South-eastern Nigeria. Data has also been derived from surveys and interviews of ADP Program Managers and NGOs. A range of qualitative and quantitative methods including inferential statistics, bivariate probit model and regression analysis were used in order to achieve the specific objectives and test hypotheses. The results show that sample respondents are dominated by small scale farmers (81% of total) owning land less than 1 ha. The average farm size is small estimated at 1.27 ha. Farmers grow multiple crops instead of a single crop, i.e., 68% of the surveyed farmers grew at least two food crops. The level of modern technology adoption is low and mixed and farmers selectively adopt components of technologies as expected and use far less than recommended dose of fertilizers in crops. Only 29% of farmers adopted both HYV seeds and fertilizers as a package. The study clearly demonstrates that inverse farm size – technology adoption, farm size – productivity, and farm size – food availability relationships exist in agriculture in this region of Nigeria; but not inverse farm size – profitability. The bivariate probit model diagnostic reveals that the decision to adopt modern technologies are significantly correlated, implying that univariate analysis of such decisions are biased, thereby, justifying use of the bivariate approach. Overall, the most dominant determinants are the positive influence of farming experience and the negative influence of remoteness of extension services on modern technology adoption. The per capita per day level of mean food produced is 12322.74 calories from one ha of land and food available for consumption is 4693.34 calories which is higher than the daily requirement of 2000 calories. Yam is produced mainly for sale while cassava is produced for consumption. Regression analysis shows that farm size and share of cassava in the total crop portfolio significantly increases food availability. A host of constraints are affecting Nigerian agriculture, which includes lack of extension agents, credit facilities, farm inputs, irrigation, and value addition and corruption, lack of support for ADP staff and ineffective government policies. Policy implications include investment in extension credit services and other infrastructure (e.g., irrigation, ADP staff), training of small farmers in business skills, promotion of modern technology, as a package as well as special projects targeted for cassava (e.g., Cassava Plus project) in order to boost modern technology adoption in food crops, as well as improving productivity, profitability and food availability at the farm-level in Nigeria.

This dissertation examines cross-category effects in consumer purchases from the big data and analytics perspectives. It uses data from Nielsen Consumer Panel and Scanner databases for its investigations. With big data analytics it becomes possible to examine the cross effects of many product categories on each other. The number of categories whose cross effects are studied is called category scale or just scale in this dissertation. The larger the category scale the higher the number of categories whose cross effects are studied. This dissertation extends research on models of cross effects by (1) examining the performance of MVP model across category scale; (2) customizing artificial neural network (ANN) techniques for large-scale cross effect analysis; (3) examining the performance of ANN across scale; and (4) developing a conceptual model of spending habits as a source of cross effect heterogeneity. The results provide researchers and managers new knowledge about using the two techniques in large category scale settings The computational capabilities required by MVP models grow exponentially with scale and thus are more significantly limited by computational capabilities than are ANN models. In our experiments, for scales 4, 8, 16 and 32, using Nielsen data, MVP models could not be estimated using baskets with 16 and more categories. We attempted to and could calibrate ANN models, on the other hand, for both scales 16 and 32. Surprisingly, the predictive results of ANN models exhibit an inverted U relationship with scale. As an ancillary result we provide a method for determining the existence and extent of non-linear own and cross category effects on likelihood of purchase of a category using ANN models. Besides our empirical studies, we draw on the mental budgeting model and impulsive spending literature, to provide a conceptualization of consumer spending habits as a source of heterogeneity in cross effect context. Finally, after a discussion of conclusions and limitations, the dissertation concludes with a discussion of open questions for future research.

本文探討大專生的學業成就，如何受到學生本身的外表吸引力以及工讀的型態所影響。本研究使用國立台灣師範大學台灣高等教育資料庫所建構的「九十二學年度大三學生問卷調查」以及「九十三學年度大專畢業生畢業後一年問卷調查」，以univariate probit model進行分析。研究結果發現：一、具外表吸引力的學生，在平均成績超過80分的機率，比外表較不具外表吸引力的學生高出5.6%；二、具外表吸引力的學生，在進入班級排名前10%的機率較不具外表吸引力的學生高出3.7%；三、雖然從事校外工讀對於學業成就有負面影響，不過從事校內工讀反而對於學業成就有正面影響。 接著以內生性分析的結果顯示，外表吸引力以及校外工讀與學業成就之間存在內生性問題。在recursive bivariate probit model估計下，外表吸引力與學業成就之間的關係仍舊為正向顯著，且男學生的外表吸引力對於學業成就之影響高於女學生；至於校外工讀與學業成就之間的關係在recursive bivariate probit model估計下反而轉變為正，表示在考慮內生性問題之後，校外工讀反而對於學業成就具有正向影響。 最後以trivariate probit model探討外表吸引力、校外工讀以及學業成就三者之間的關係，結果發現在控制外表吸引力下，校外工讀對於學業成就的影響差異並不大，工讀的負面效果並不會因為具有外表吸引力而有所減緩。

Approved for public release; distribution is unlimited. / This thesis investigates the effect of marital and family status on the performance and job productivity of male U.S. Marine Corps officers. The analysis includes evaluation of fitness reports, retention, and promotion to O-4 and O-5 ranks as performance measures. The primary goal is to examine the existence of any marriage premium on officers' performance and productivity and to investigate potential causal hypotheses. The personnel database used for the analysis includes more than 27,000 male Marine officers who entered the Marine Corps between FY 1980 and 1999. After controlling for selection, estimating fixed effects and using panel data in order to capture timely-varying effects, this study finds that there is a marriage premium for all performance measures. The thesis rejects the explanation that such premiums are due to supervisor favoritism. Moreover, married male officers obtain higher fitness report scores, higher promotion probabilities, and higher retention probabilities than single officers. Each additional year spent in marriage increases fitness report scores and retention probabilities. Having additional non-spousal dependents increase fitness report scores and retention probabilities. On the other hand, being a currently single but "to-be-married" officer yields higher premium, as married officers, for all productivity and performance indicators. This supports selectivity into marriage as a partial explanation of the source of the marriage premium. / Lieutenant Junior Grade, Turkish Navy / First Lieutenant, Turkish Army

台灣產險市場自2009年4月費率自由化第三階段實施後，費率訂定依產險公司自家損失經驗及費用控制而訂，各產險業者必須在相關監理配套措施及自律規範下，進行市場費率自由定價及防止惡性競爭。然而隨著投保率的上升，損失率卻沒有獲得改善。有鑑於此，探究使得汽車第三人責任保險市場上損失率居高不下的原因，可能是由於訊息不對稱(Asymmetric Information)所致。 是故，本研究採用國內某家產物保險公司的樣本，針對台灣汽車第三人責任保險上的訊息不對稱問題進行實證研究。除了探討市場上是否存在訊息不對稱問題，更重要的是，嘗試區分在不同通路銷售保單上，可能面臨的訊息不對稱問題的影響程度。本研究的內容在於：(1)以與保險公司本身關係親疏不同之通路，銷售汽車保險保單時，實證研究在保單上所可能面臨的訊息不對稱問題的影響程度。 (2)依循Dionne et al的兩階段估計法(Two-Stage Method)，對訊息不對稱問題進行檢定。分別使用Probit Regression與Negative Binomial Regression建立實證模型，多重檢證訊息不對稱是否存在，確保了研究結論的穩健性和可靠性。(3)我們成功辨識逆選擇或道德風險所形成訊息不對稱，在不同通路投保人群體中的顯著性有所不同，這個發現增益了過去國內有關人車風險分類，與費率釐訂等定性研究的結論。

The thesis investigates determinants of participation in the supplementary pension savings scheme in the Czech Republic and estimates their change with respect to the policy intervention realized in 2013. Using the time series of cross-sectional microeconomic data provided by the Statistics on Income and Living Conditions, the probability of participation and the level of contributions are estimated separately by probit and multiple linear regressions, respectively. The estimated coefficients of both models are tested for structural differences caused by the policy change, employing the pooled dataset of multiple years with additional coefficients to treat the compared period. The analysis confirms that income, age, education and economic activity have a positive effect on both the probability of participation and expected level of contributions. Whereas gender differences for the level of contributions have not been detected, single women on average show, ceteris paribus, 4.6 percentage points higher probability of participation than single men. Unexpectedly high level of activity was observed in case of retired individuals, who in 2014 represented approximately 15% of all participants and collected 20% of the credited direct state subsidy. With respect to the 2013 policy change, no evidence of a...