USING PRINCIPAL COMPONENT ANALYSIS (PCA) TO OBTAIN AUXILIARY VARIABLES FOR MISSING DATA IN LARGE DATA SETS

The purpose of this dissertation is to address an important issue in the imputation of missing data in large data sets. The issue can arise in any analysis in which auxiliary variables are used to inform a modern missing data handling procedure (e.g., FIML, MI) to support the missing at random assumption, reduce bias and decrease standard errors. The problem is that researchers suggest an "inclusive strategy" where as many auxiliary variables are included as possible. However, the model becomes more complex with the addition of each additional auxiliary variable, so there is a practical limit to the number of auxiliary variables that can be successfully included. Beyond this limit, the model will fail to converge. Large data projects can present a challenge because it is possible to have hundreds of potential auxiliary variables to inform the missing data handling procedure, especially when non-linear information is included. The dissertation is divided into the following sections: 1) a brief discussion of the issue of missing data; 2) a review of the history of missing data including theory and existing solutions regarding handling missingness; 3) an assessment of the use of auxiliary variables in missing data handling; 4) a discussion of convergence failure with modern missing data methods; 5) a basic introduction to principal component analysis; 6) the introduction of an alternative strategy to address the large number of auxiliary variables issue; and finally, 7) a demonstration of the potential of the principal component scores as auxiliary variables approach by applying it to the analysis of simulated and empirical data

Preliminary study of illumination levels in university and elementary classrooms in Campina Grande, Brazil

The purpose of our study was to provide preliminary data on light levels used in university and elementary school classrooms in Campina Grande, Brazil with the aim of providing Brazilian politicians and educators with data to support continued educational initiatives in northeast Brazil. The data were gathered at the Universidade Federal de Campina Grande (UFCG) and compared with a sample of classrooms at Oklahoma State University (OSU) in Stillwater Oklahoma. The results indicated that many seats within UFCG classrooms met or exceeded minimum standards but significant numbers did not. Moreover, compared to classrooms at OSU, UFCG classrooms are not as highly illuminated and the Brazilian elementary classrooms examined did not meet minimum illumination standards.Peer reviewedPsychologyZoolog

Price survey comparison of alcoholic beverages with the five basic food groups in Paraiba, Brazil

The study of alcohol abuse is relatively new in Brazil. Government estimates suggest that 11.2% of the Brazilian population is alcohol dependent. Problems associated with alcohol dependence include domestic violence, increased risk of traffic accidents, poor self-esteem and weak academic performance. A factor known to correlate with alcohol abuse in 12-17 year olds is to have the money necessary to purchase alcoholic beverages. No data is available, however, on the price of alcoholic beverages. The objective of the present study was to provide data on price and to compare the price of alcoholic beverages to basic food items in the Brazilian diet. We also had interest in studying a population in the northeast region of Brazil. This region is the poorest in Brazil, has the highest percentage of alcohol dependency and is seldom the focus of research on dependency. We report that the prices of many alcoholic beverages are less than the price of basic food items. Prices of alcoholic beverages including beer, wine and spirits were compared to the prices of select food items as represented in the Food Pyramid. Food items were selected from the categories of Grain, Dairy, Fruit, Meat and Vegetable. Data was gathered from 32 supermarkets in 8 cities in the northeast state of Paraiba. The price of alcohol is generally less expensive than most basic food group items, especially brands of cachaca (a spirit distilled from sugar cane) and beer. Data on price should be considered in any alcohol dependency program in Brazil.Peer reviewedPsycholog

Attrition in developmental psychology: A review of modern missing data reporting and practices

Inherent in applied developmental sciences is the threat to validity and generalizability due to missing data as a result of participant drop-out. The current paper provides an overview of how attrition should be reported, which tests can examine the potential of bias due to attrition (e.g., t-tests, logistic regression, Little\u27s MCAR test, sensitivity analysis), and how it is best corrected through modern missing data analyses. To amend this discussion of best practices in managing and reporting attrition, an assessment of how developmental sciences currently handle attrition was conducted. Longitudinal studies (n = 541) published from 2009-2012 in major developmental journals were reviewed for attrition reporting practices and how authors handled missing data based on recommendations in the Publication Manual of the American Psychological Association (APA, 2010). Results suggest attrition reporting is not following APA recommendations, quality of reporting did not improve since the APA publication, and a low proportion of authors provided sufficient information to convey that data properly met the MAR assumption. An example based on simulated data demonstrates bias that may result from various missing data mechanisms in longitudinal data, the utility of auxiliary variables for the MAR assumption, and the need for viewing missingness along a continuum from MAR to MNAR