Thesis (Ph. D.)--University of Texas Health Science Center at Houston, School of Public Health, 2008. / "May 2008." Source: Dissertation Abstracts International, Volume: 69-03, Section: B, page: 1561. Adviser: Luisa Franzini. Includes bibliographical references.

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This research develops a framework to estimate the effective sample size of Global Positioning System (GPS) based panel surveys in urban travel behavior studies for a variety of planning purposes. Recent advances in GPS monitoring technologies have made it possible to implement panel surveys with lengths of weeks, months or even years. The many advantageous features of GPS-based panel surveys make such surveys attractive for travel behavior studies, but the higher cost of such surveys compared to conventional one-day or two-day paper diary surveys requires scrutiny at the sample size planning stage to ensure cost-effectiveness. The sample size analysis in this dissertation focuses on three major aspects in travel behavior studies: 1) to obtain reliable means for key travel behavior variables, 2) to conduct regression analysis on key travel behavior variables against explanatory variables such as demographic characteristics and seasonal factors, and 3) to examine impacts of a policy measure on travel behavior through before-and-after studies. The sample size analyses in this dissertation are based on the GPS data collected in the multi-year Commute Atlanta study. The sample size analysis with regard to obtaining reliable means for key travel behavior variables utilizes Monte Carlo re-sampling techniques to assess the trend of means against various sample size and survey length combinations. The basis for the framework and methods of sample size estimation related to regression analysis and before-and-after studies are derived from various sample size procedures based on the generalized estimating equation (GEE) method. These sample size procedures have been proposed for longitudinal studies in biomedical research. This dissertation adapts these procedures to the design of panel surveys for urban travel behavior studies with the information made available from the Commute Atlanta study. The findings from this research indicate that the required sample sizes should be much larger than the sample sizes in existing GPS-based panel surveys. This research recommends a desired range of sample sizes based on the objectives and survey lengths of urban travel behavior studies.

This thesis investigates the sensitivity of derived monetary valuations of the well-being effects of non-market goods, by considering, in turn, the four components that contribute to these calculations. Comparisons are made to the current subjective well-being (SWB) literature by altering one component at a time in a willingness to pay (WTP) function, in addition to varying the estimator used when calculating WTP. The first component varied is the measure of income used; a more robust, up-to-date measure is proposed that takes into account household size, economies of scale and composition, plus other improvements over current income scaling approaches including equivalence scales. Secondly, anticipation and adaptation effects are examined, in order to allow for the dynamics of SWB in WTP valuations. Thirdly, due to the ordered nature of the dependent variable, the effects of both cardinal and ordinal models on WTP derivations are investigated. Such models include the ordered logit fixed effects (FE) model (see for example Das and Van Soest (1999), Ferrer-i-Carbonell and Frijters (2004) and Baetschmann et al. (2011)). The final input to be varied is whether income endogeneity is accounted for. A control function approach is used in this case. A key finding is that all four inputs in the WTP calculation contribute significantly to the estimated WTP values. However, the degree to which each input influences the variation in WTP values differs substantially. The three main contributing factors to WTP variations are the income variable chosen, anticipation and adaptation effects, and controlling for endogeneity. Additionally, this thesis proposes a new way to define WTP that is also valid for ordered estimators. Whilst the standard WTP approach relies simply on coefficient ratios at a point in time, the method proposed here uses the finding that statistically significant anticipation and adaptation effects, along with adaptation to all non-market events (except for unemployment) suggest that there are concerns with taking WTP values as yearly valuations that assume constant effects on SWB. By instead defining WTP as the summation of the value of all WTP effects over all lag and lead effect periods, the total value of an event can be calculated. This definition presents further weaknesses of the original method by showing that because of significant lag and lead effects for events such as divorce and widowhood, these events have substantially larger WTP values than first thought. This leads to the major finding in this study that rank orders are not preserved when controlling for income endogeneity, even when comparing two model specifications that are identical in all other respects. Therefore, despite absolute WTP valuations appearing more similar for linear and ordered estimators when a more appropriate model specification is in place, the rank orders are affected. This finding argues against papers such as Powdthavee and van den Berg (2011) that find that rank orders are preserved for WTP valuations when modelling SWB. In conclusion, given rank orders are generally not preserved when a small change is made in the model specification, the validity of the WTP method is significantly reduced. Finally, the above methodology is applied to education, with the main contribution to the education literature being that the positive effects on SWB from education only exist in terms of lead effects.

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本研究探討影響學生學業成就的學校、家庭、學生個人及背景因素，研究中以後設分析的方法計算出許多自變項的效應量大小。本研究的資料取自台灣教育長期追蹤資料庫（TEPS），包括2868名學生在2001年至2007年間接受的四波追蹤調查資料。研究結果發現，學校、家庭、學生個人及背景因素對學業成就之平均效應量具有顯著差異，其中以學生的「先前學業成就」具有最大的效應量，對綜合能力、數學能力及一般分析能力的效應量分別是2.39、1.45和1.90；其次為「背景因素」（效應量分別為.65、.53、.59）；再其次則為「家庭因素」及「學生投入」，但此兩者效應量小，且彼此間無顯著差異；而學校因素的平均效應量最小。最後，本研究針對研究結果提出多項教育實務的建議。 / The purpose of this study is to examine the longitudinal effects of school, family, student, and demographic factors on students’ academic achievement. A method of meta-analysis was used to estimate the magnitude of the effect size of various dependent variables. The data was obtained from Taiwan Education Panel Survey (TEPS). The members of the tracked panel of 2868 high school students were selected as samples for this present research. The tracked panel received four waves of questionnaires and standard tests from 2001 to 2007. The results of the present analysis shows significant differences between the mean effect sizes of the factors associated with academic achievement, and that students’ prior achievement had the largest effect size of 2.39, 1.45, and 1.90, respectively, based on the comprehensive ability score, the general analytic ability score, and the mathematic ability score. The demographic factor showed the second largest mean effect size (.65, .53, .59), larger than that of the family factor and students’ engagement, which both showed small effect without significant differences from each other. And the school factor showed the least mean effect size. In addition, it was found that the mean effect of all the variables based on the comprehensive ability score (.43) was significantly larger than that based on the general analytic ability score and on the mathematic ability score, specifically. Practical implications and suggestions are given in the present research after the general discussion of the research findings.

本研究以TEPS資料庫第二、三波追蹤樣本為資料來源，使用多元迴歸分析中的OLS（ordinal least squares）最小平方法，分析不同管教方式之父母比較行為如何影響子女之綜合能力。刪除作答不全的缺失值後，共計取得有效樣本為2,595人。 研究結果顯示：父母管教方式若以雙向度作為分類，以高反應（74.6％）與高要求（69.2％）者居多，綜合兩大面向後，有52.40％的父母採取開明權威型的管教方式，有22.20％的父母為專制權威型，有16.90％的父母為寬鬆放任型，有8.50％的父母是忽視冷漠型。此外，父母最常把子女與其同班同學（45.5％）進行比較，其次依序為鄰居小孩、同事或朋友小孩（42.0％）、同年齡的親戚（37.0％）、兄弟姊妹（26.9％），父母最少拿自己小時候（18.8％）與子女相比。 經由多元迴歸分析之後得知，無論是開明權威、專制權威、寬鬆放任或忽視冷漠型的父母，凡拿子女與其「同班同學」比較者，子女的綜合能力越高，達到統計顯著水準；但是當父母持專制權威的管教方式時，無論有無加入控制變項（子女性別、父母教育程度和家庭月收入），有與「同班同學」和「父母小時候」比較者，其綜合能力顯著越高，但與「同年齡親戚」比較者，其綜合能力顯著越低。 / The research was to explore the effects of parenting style, parental comparison, and the interaction of them on children’s general ability. Data were collected from Taiwan Education Panel Survey (TEPS), the core panel in the second and the third wave. Total number of the students from high school reduced to 2,595 people after listwise deletion. We explored the effects by using ordinal least squares in the multiple regression analysis. The results showed that there were 74.6% high-respective parents, and 69.2% high-demanding ones. Mixed with the two dimensions, demanding and responsive, there were 52.40% authoritative parents, 22.20% authoritarian ones, 16.90% indulgent ones, and 8.50% neglectful ones. Besides, parents compared their children with their classmates (45.5%), neighbors (42.0%), cousins (37.0%), siblings (26.9%), and parents’ childhood (18.8%). After regression, the results showed in the following ways. First, no matter what the parenting style was, children who were compared with classmates had significantly higher ability. Whether adding the control variables like children’ gender, parents’ education level and family monthly income or not, when parents were authoritarian, children compared with classmates and parents’ childhood had significantly higher ability. Meanwhile, if they were compared with cousins, then they had significantly lower ability. Keywords: Taiwan Education Panel Survey (TEPS), multiple regression analysis, parenting style, social comparison, general ability

學習表現為教育社會學中的重要議題，其中城鄉間的學習表現差距受到重視。過去研究認為家庭背景與地區的教育資源是影響學生學習表現的主要因素，然而這些研究缺乏班級因素與同儕效果的分析。因此本研究使用台灣教育長期追蹤資料庫（Taiwan Education Panel Survey, TEPS）在2001年與2003年的國中生樣本，以階層線性模型（Hierarchical Linear Modeling, HLM）分析國一班級同儕學習投入對國三數學表現的影響，學習投入以學生為課業所付出的時間為指標。分析結果發現：(1)學生數學表現的總變異中有24%來自班級因素的影響，76%為學生因素。(2)國三數學表現、個人學習投入與班級同儕學習投入有城鄉差距。(3)在控制其他變項下，個人學習投入、班級同儕學習投入對數學表現有正向效果。(4)班級所在地區的都市化程度透過班級同儕學習投入間接影響國三數學表現。 / Academic performance has been an important topic of research on educational sociology for a long time, while urban-rural differences have been already well documented in literatures. In the past, the literature indicated that the key factors to affecting academic performance are family background and the educational resources. But these researches have ignored the factors of class level and peer effects. In this study, the data are from Taiwan Education Panel Survey (TEPS) in 2001 and 2003, use Hierarchical Linear Modeling (HLM) to assess how peer engagement affects junior high students’ mathematics performance. The time students spend in studying is an index of engagement. The main finding are: (1) This research model accounts for 76% of the variation in student level and for 24% of the class variation in class level with regard to mathematical performance. (2) Students in the urban and rural city show a differences in their mathematics performance, student’s own engagement and peer engagement. (3) When controlling variables, student’s own engagement and peer engagement have positive effect on mathematics performance. (4) Urbanization levels indirectly affect mathematics performance through peer engagement.

本研究採用「台灣教育長期追蹤資料庫」（TEPS）調查結果，對台灣地區高中職學生個人特徵、家庭背景以及學生生活進行次級資料分析，探討各種因素與學業表現之關聯性。 　　本研究選取資料庫中之9,750樣本數，以資料庫綜合分析能力測驗成績作為應變數，選取性別及手足數目等12個自變數，以Logit Model為實證模型分析，再以Ordered Probit Model進行實證結果穩健性檢驗（Robustness Check），發現兩者結果呈現一致性，本研究發現： 一、男性成績較女性成績為佳，曾經或現在就讀資優班者成績較為優異。 二、家庭手足數目對學生學業成績表現有負向影響，雙親教育程度、家庭收入愈高及家庭文化資本愈豐富對子女學業表現有正向顯著影響；家庭親子關係、父母閱讀頻率對於子女學業表現則無顯著影響。 三、補習、參加社團活動以及校隊培訓對學業成績有正向影響；打工及結交行為偏差朋友則對學業成績有負向影響。 　　本研究提出教育政策方向建議如下： 一、建議文創產業主管機關以差別取價之價格誘因方式提高親子參與藝文活動之意願，並持續鼓勵文創產業提供學校學生及家長參與藝文展演活動機會。 二、教育主管機關應持續執行對（中）低收入戶子女學雜費補助之政策，並建立對高中職學校社團活動之管理制度，另應加強學生品性教育管理。 / This study analyzes the association between personal characteristics, family background, the life of students and academic achievement of students in senior high school. The data have adapted Taiwan Education Panel Survey (TEPS). The research has used 9,750 samples in the database. The dependent variable is the test scores of students while the independent variables are gender, the number of sibling, etc. This study has used Logit Model for empirical analysis and Ordered Probit Model for robustness check of the results. The research findings indicate that both models have similar conclusions, which are shown as follows. Firstly, the academic achievement of males is better than that of females. Moreover, students who are in the gifted and talented class have a better performance than those who are not in. Secondly, the number of sibling has a negative effect on academic achievement; whereas the education background of the parents, income and cultural capital of the family are as the opposite. The frequency of reading and the relationship between parents and children have no significant influence on academic achievement. Thirdly, the student who goes to cram school or participates in extracurricular activities has a positive influence on his/her academic achievement. However, the student with the part-time job or bad-behavior friends has a negative influence on his/her academic achievement. Therefore, the authorities should encourage parents and their children to participate in cultural activities through offering economic incentives and the tuition subsidies for low-income households continuously.

本研究使用「臺灣教育長期追蹤資料庫」第二波（2003）國三與第三波（2005）高二的CP追蹤數據，採用反事實模型框架下的傾向分數配對法估計單一性別環境對臺灣高中女生選組行爲（自然組／社會組）的因果效應。使用學生進入高中前的國三資料，本研究在學生因素，家庭因素和學校、班級因素三個方面充分平衡處置組（進入女校）和控制組（進入男女合校）的樣本，使配對樣本之間除了進入女校或進入男女合校之外，在以上三個方面儘可能相等，嘗試克服觀察性數據因選擇性偏誤問題對因果效應的估計帶來的阻礙。結果顯示，在進行傾向分數配對後，處置組和控制組之間達到了很好的平衡，進入女校的女生與進入男女合班的男女合校中的女生相比，女校顯著地促進了高中女生選自然組的機率，然而該效應在數學成績水平不同的女生中存在異質性，女校顯著地促進了數學成績處於高水平的女生的選擇自然組的行爲。作爲教育分流的重要組成部分，臺灣高中生選組行爲的性別隔離長期存在，選組行爲與學生未來大學科系選擇和職業選擇關係密切，自然組中低比例的女生組成顯現出隱藏的教育機會不平等。該現象長期存在的背後因素，除了學生個人因素和學生家庭背景因素帶來的影響，本研究關注學校這一角色對高中女生選組行爲的影響。 / Based on the Taiwan Educational Panel Survey’s core panel data from wave 2 (junior high school/9th grade) and wave 3 (high school/11th grade), researcher applies the propensity score analysis in counterfactual framework to study the causal effect of single-sex schooling on high school girls’ curriculum tracking (science track or humanity track) selection. Observational data always be the obstacles of making the causal analysis because it's lacking random assignment and being under threat of selection bias and unobserved variables. Using the pretreatment variables from students in 9th grade, students in the treatment group were matched with those in control groups by the individual factors, family factors and school, classroom environment factors. After matching, students come from different groups are supposed to be relatively equivalent on all the matching variables except for attending single-sex school or not. The researcher can make suitable comparison and prediction between well-matched samples. The result shows that more girls in single-sex high schools tend to choose science track. Effect of single-sex schooling is not the same among girls with different level of math scores. It benefits girls with top math performance significantly. As an important part of the educational tracking system, alternative curriculum tracking selection in Taiwan high school is worth noteworthy. The long lasting gender segregation is closely associated with students college major as well as occupation selection and it reveals the hidden educational inequality between gender. Other than focusing on the individual and family background effect on high school girls’ curriculum tracking selection, this study highlights the school effect on it.