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  Partner: UNT Libraries
 Department: Department of Educational Psychology
 Degree Discipline: Educational Research
 Collection: UNT Theses and Dissertations
Attenuation of the Squared Canonical Correlation Coefficient Under Varying Estimates of Score Reliability

Attenuation of the Squared Canonical Correlation Coefficient Under Varying Estimates of Score Reliability

Date: August 2010
Creator: Wilson, Celia M.
Description: Research pertaining to the distortion of the squared canonical correlation coefficient has traditionally been limited to the effects of sampling error and associated correction formulas. The purpose of this study was to compare the degree of attenuation of the squared canonical correlation coefficient under varying conditions of score reliability. Monte Carlo simulation methodology was used to fulfill the purpose of this study. Initially, data populations with various manipulated conditions were generated (N = 100,000). Subsequently, 500 random samples were drawn with replacement from each population, and data was subjected to canonical correlation analyses. The canonical correlation results were then analyzed using descriptive statistics and an ANOVA design to determine under which condition(s) the squared canonical correlation coefficient was most attenuated when compared to population Rc2 values. This information was analyzed and used to determine what effect, if any, the different conditions considered in this study had on Rc2. The results from this Monte Carlo investigation clearly illustrated the importance of score reliability when interpreting study results. As evidenced by the outcomes presented, the more measurement error (lower reliability) present in the variables included in an analysis, the more attenuation experienced by the effect size(s) produced in the analysis, in this ...
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Convergent Validity of Variables Residualized By a Single Covariate: the Role of Correlated Error in Populations and Samples

Convergent Validity of Variables Residualized By a Single Covariate: the Role of Correlated Error in Populations and Samples

Date: May 2013
Creator: Nimon, Kim
Description: This study examined the bias and precision of four residualized variable validity estimates (C0, C1, C2, C3) across a number of study conditions. Validity estimates that considered measurement error, correlations among error scores, and correlations between error scores and true scores (C3) performed the best, yielding no estimates that were practically significantly different than their respective population parameters, across study conditions. Validity estimates that considered measurement error and correlations among error scores (C2) did a good job in yielding unbiased, valid, and precise results. Only in a select number of study conditions were C2 estimates unable to be computed or produced results that had sufficient variance to affect interpretation of results. Validity estimates based on observed scores (C0) fared well in producing valid, precise, and unbiased results. Validity estimates based on observed scores that were only corrected for measurement error (C1) performed the worst. Not only did they not reliably produce estimates even when the level of modeled correlated error was low, C1 produced values higher than the theoretical limit of 1.0 across a number of study conditions. Estimates based on C1 also produced the greatest number of conditions that were practically significantly different than their population parameters.
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Determination of the optimal number of strata for bias reduction in propensity score matching.

Determination of the optimal number of strata for bias reduction in propensity score matching.

Date: May 2010
Creator: Akers, Allen
Description: Previous research implementing stratification on the propensity score has generally relied on using five strata, based on prior theoretical groundwork and minimal empirical evidence as to the suitability of quintiles to adequately reduce bias in all cases and across all sample sizes. This study investigates bias reduction across varying number of strata and sample sizes via a large-scale simulation to determine the adequacy of quintiles for bias reduction under all conditions. Sample sizes ranged from 100 to 50,000 and strata from 3 to 20. Both the percentage of bias reduction and the standardized selection bias were examined. The results show that while the particular covariates in the simulation met certain criteria with five strata that greater bias reduction could be achieved by increasing the number of strata, especially with larger sample sizes. Simulation code written in R is included.
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A Hierarchical Regression Analysis of the Relationship Between Blog Reading, Online Political Activity, and Voting During the 2008 Presidential Campaign

A Hierarchical Regression Analysis of the Relationship Between Blog Reading, Online Political Activity, and Voting During the 2008 Presidential Campaign

Date: December 2010
Creator: Lewis, Mitzi
Description: The advent of the Internet has increased access to information and impacted many aspects of life, including politics. The present study utilized Pew Internet & American Life survey data from the November 2008 presidential election time period to investigate the degree to which political blog reading predicted online political discussion, online political participation, whether or not a person voted, and voting choice, over and above the predication that could be explained by demographic measures of age, education level, gender, income, marital status, race/ethnicity, and region. Ordinary least squares hierarchical regression revealed that political blog reading was positively and statistically significantly related to online political discussion and online political participation. Hierarchical logistic regression analysis indicated that the odds of a political blog reader voting were 1.98 the odds of a nonreader voting, but vote choice was not predicted by reading political blogs. These results are interpreted within the uses and gratifications framework and the understanding that blogs add an interpersonal communication aspect to a mass medium. As more people use blogs and the nature of the blog-reading audience shifts, continuing to track and describe the blog audience with valid measures will be important for researchers and practitioners alike. Subsequent potential effects ...
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Investigating the hypothesized factor structure of the Noel-Levitz Student Satisfaction Inventory: A study of the student satisfaction construct.

Investigating the hypothesized factor structure of the Noel-Levitz Student Satisfaction Inventory: A study of the student satisfaction construct.

Date: December 2008
Creator: Odom, Leslie R.
Description: College student satisfaction is a concept that has become more prevalent in higher education research journals. Little attention has been given to the psychometric properties of previous instrumentation, and few studies have investigated the structure of current satisfaction instrumentation. This dissertation: (a) investigated the tenability of the theoretical dimensional structure of the Noel-Levitz Student Satisfaction Inventory™ (SSI), (b) investigated an alternative factor structure using explanatory factor analyses (EFA), and (c) used multiple-group CFA procedures to determine whether an alternative SSI factor structure would be invariant for three demographic variables: gender (men/women), race/ethnicity (Caucasian/Other), and undergraduate classification level (lower level/upper level). For this study, there was little evidence for the multidimensional structure of the SSI. A single factor, termed General Satisfaction with College, was the lone unidimensional construct that emerged from the iterative CFA and EFA procedures. A revised 20-item model was developed, and a series of multigroup CFAs were used to detect measurement invariance for three variables: student gender, race/ethnicity, and class level. No measurement invariance was noted for the revised 20-item model. Results for the invariance tests indicated equivalence across the comparison groups for (a) the number of factors, (b) the pattern of indicator-factor loadings, (c) the factor loadings, ...
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Missing Data Treatments at the Second Level of Hierarchical Linear Models

Missing Data Treatments at the Second Level of Hierarchical Linear Models

Date: August 2011
Creator: St. Clair, Suzanne W.
Description: The current study evaluated the performance of traditional versus modern MDTs in the estimation of fixed-effects and variance components for data missing at the second level of an hierarchical linear model (HLM) model across 24 different study conditions. Variables manipulated in the analysis included, (a) number of Level-2 variables with missing data, (b) percentage of missing data, and (c) Level-2 sample size. Listwise deletion outperformed all other methods across all study conditions in the estimation of both fixed-effects and variance components. The model-based procedures evaluated, EM and MI, outperformed the other traditional MDTs, mean and group mean substitution, in the estimation of the variance components, outperforming mean substitution in the estimation of the fixed-effects as well. Group mean substitution performed well in the estimation of the fixed-effects, but poorly in the estimation of the variance components. Data in the current study were modeled as missing completely at random (MCAR). Further research is suggested to compare the performance of model-based versus traditional MDTs, specifically listwise deletion, when data are missing at random (MAR), a condition that is more likely to occur in practical research settings.
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Parent Involvement and Science Achievement: A Latent Growth Curve Analysis

Parent Involvement and Science Achievement: A Latent Growth Curve Analysis

Date: August 2011
Creator: Johnson, Ursula Yvette
Description: This study examined science achievement growth across elementary and middle school and parent school involvement using the Early Childhood Longitudinal Study – Kindergarten Class of 1998 – 1999 (ECLS-K). The ECLS-K is a nationally representative kindergarten cohort of students from public and private schools who attended full-day or half-day kindergarten class in 1998 – 1999. The present study’s sample (N = 8,070) was based on students that had a sampling weight available from the public-use data file. Students were assessed in science achievement at third, fifth, and eighth grades and parents of the students were surveyed at the same time points. Analyses using latent growth curve modeling with time invariant and varying covariates in an SEM framework revealed a positive relationship between science achievement and parent involvement at eighth grade. Furthermore, there were gender and racial/ethnic differences in parents’ school involvement as a predictor of science achievement. Findings indicated that students with lower initial science achievement scores had a faster rate of growth across time. The achievement gap between low and high achievers in earth, space and life sciences lessened from elementary to middle school. Parents’ involvement with school usually tapers off after elementary school, but due to parent school ...
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A Quantitative Modeling Approach to Examining High School, Pre-Admission, Program, Certification and Career Choice Variables in Undergraduate Teacher Preparation Programs

A Quantitative Modeling Approach to Examining High School, Pre-Admission, Program, Certification and Career Choice Variables in Undergraduate Teacher Preparation Programs

Date: December 2007
Creator: Williams, Cynthia Savage
Description: The purpose of this study was to examine if there is an association between effective supervision and communication competence in divisions of student affairs at Christian higher education institutions. The investigation examined chief student affairs officers (CSAOs) and their direct reports at 45 institutions across the United States using the Synergistic Supervision Scale and the Communication Competence Questionnaire. A positive significant association was found between the direct report's evaluation of the CSAO's level of synergistic supervision and the direct report's evaluation of the CSAO's level of communication competence. The findings of this study will advance the supervision and communication competence literature while informing practice for student affairs professionals. This study provides a foundation of research in the context specific field of student affairs where there has been a dearth of literature regarding effective supervision. This study can be used as a platform for future research to further the understanding of characteristics that define effective supervision.
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Spatial Ability, Motivation, and Attitude of Students as Related to Science Achievement

Spatial Ability, Motivation, and Attitude of Students as Related to Science Achievement

Date: May 2011
Creator: Bolen, Judy Ann
Description: Understanding student achievement in science is important as there is an increasing reliance of the U.S. economy on math, science, and technology-related fields despite the declining number of youth seeking college degrees and careers in math and science. A series of structural equation models were tested using the scores from a statewide science exam for 276 students from a suburban north Texas public school district at the end of their 5th grade year and the latent variables of spatial ability, motivation to learn science and science-related attitude. Spatial ability was tested as a mediating variable on motivation and attitude; however, while spatial ability had statistically significant regression coefficients with motivation and attitude, spatial ability was found to be the sole statistically significant predictor of science achievement for these students explaining 23.1% of the variance in science scores.
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Stratified item selection and exposure control in unidimensional adaptive testing in the presence of two-dimensional data.

Stratified item selection and exposure control in unidimensional adaptive testing in the presence of two-dimensional data.

Date: August 2009
Creator: Kalinowski, Kevin E.
Description: It is not uncommon to use unidimensional item response theory (IRT) models to estimate ability in multidimensional data. Therefore it is important to understand the implications of summarizing multiple dimensions of ability into a single parameter estimate, especially if effects are confounded when applied to computerized adaptive testing (CAT). Previous studies have investigated the effects of different IRT models and ability estimators by manipulating the relationships between item and person parameters. However, in all cases, the maximum information criterion was used as the item selection method. Because maximum information is heavily influenced by the item discrimination parameter, investigating a-stratified item selection methods is tenable. The current Monte Carlo study compared maximum information, a-stratification, and a-stratification with b blocking item selection methods, alone, as well as in combination with the Sympson-Hetter exposure control strategy. The six testing conditions were conditioned on three levels of interdimensional item difficulty correlations and four levels of interdimensional examinee ability correlations. Measures of fidelity, estimation bias, error, and item usage were used to evaluate the effectiveness of the methods. Results showed either stratified item selection strategy is warranted if the goal is to obtain precise estimates of ability when using unidimensional CAT in the presence of ...
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