This study compared the estimates of reliability made using one, two, three, four, five, and unlimited consecutive failures as ceiling rules in scoring a mathematics achievement test which is part of the Iowa Tests of Basic Skill (ITBS), Form 8. There were 700 students randomly selected from a population (N=2640) of students enrolled in the eight grades in a large urban school district in the southwestern United States. These 700 students were randomly divided into seven subgroups so that each subgroup had 100 students. The responses of all those students to three subtests of the mathematics achievement battery, which included mathematical concepts (44 items), problem solving (32 items), and computation (45 items), were analyzed to obtain the item difficulties and a total score for each student. The items in each subtest then were rearranged based on the item difficulties from the highest to the lowest value. In each subgroup, the method using one, two, three, four, five, and unlimited consecutive failures as the ceiling rules were applied to score the individual responses. The total score for each individual was the sum of the correct responses prior to the point described by the ceiling rule. The correct responses after the ceiling …

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, …

The problem of this study was to examine the equivalency of two different types of criterion-referenced item-selection techniques on simulated data as item pools varied in degrees of item difficulty. A pretest-posttest design was employed in which pass-fail scores were randomly generated for item pools of twenty-five items. From the item pools, the two techniques determined which items were to be used to make up twelve-item criterion-referenced tests. The twenty-five items also were rank ordered according to the discrimination power of the two techniques.

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 …

The purpose of this investigation was to determine the influence of item response theory and different types of judges on a standard. The iterative Angoff standard setting method was employed by all judges to determine a cut-off score for a public school district-wide criterion-reformed test. The analysis of variance of the effect of judge type and standard setting method on the central tendency of the standard revealed the existence of an ordinal interaction between judge type and method. Without any knowledge of p-values, one judge group set an unrealistic standard. A significant disordinal interaction was found concerning the effect of judge type and standard setting method on the variance of the standard. A positive covariance was detected between judges' minimum pass level estimates and empirical item information. With both p-values and b-values, judge groups had mean minimum pass levels that were positively correlated (ranging from .77 to .86), regardless of the type of information given to the judges. No differences in correlations were detected between different judge types or different methods. The generalizability coefficients and phi indices for 12 judges included in any method or judge type were acceptable (ranging from .77 to .99). The generalizability coefficient and phi index …

Random number generators (RNGs) are widely used in conducting Monte Carlo simulation studies, which are important in the field of statistics for comparing power, mean differences, or distribution shapes between statistical approaches. Statistical results, however, may differ when different random number generators are used. Often older methods have been blindly used with no understanding of their limitations. Many random functions supplied with computers today have been found to be comparatively unsatisfactory. In this study, five multiplicative linear congruential generators (MLCGs) were chosen which are provided in the following statistical packages: RANDU (IBM), RNUN (IMSL), RANUNI (SAS), UNIFORM(SPSS), and RANDOM (BMDP). Using a personal computer (PC), an empirical investigation was performed using five criteria: period length before repeating random numbers, distribution shape, correlation between adjacent numbers, density of distributions and normal approach of random number generator (RNG) in a normal function. All RNG FORTRAN programs were rewritten into Pascal which is more efficient language for the PC. Sets of random numbers were generated using different starting values. A good RNG should have the following properties: a long enough period; a well-structured pattern in distribution; independence between random number sequences; random and uniform distribution; and a good normal approach in the normal …

Two procedures for detection of differential item functioning (DIF) for polytomous items were generalized to detection of differential testlet functioning (DTLF). The methods compared were the logistic discriminant function analysis procedure for uniform and non-uniform DTLF (LDFA-U and LDFA-N), and the Mantel score test procedure. Further analysis included comparison of results of DTLF analysis using the Mantel procedure with DIF analysis of individual testlet items using the Mantel-Haenszel (MH) procedure. Over 600 chi-squares were analyzed and compared for rejection of null hypotheses. Samples of 500, 1,000, and 2,000 were drawn by gender subgroups from the NELS:88 data set, which contains demographic and test data from over 25,000 eighth graders. Three types of testlets (totalling 29) from the NELS:88 test were analyzed for DTLF. The first type, the common passage testlet, followed the conventional testlet definition: items grouped together by a common reading passage, figure, or graph. The other two types were based upon common content and common process. as outlined in the NELS test specification.

The common practice for testing measurement invariance is to constrain parameters to be equal over groups, and then evaluate the model-data fit to reject or fail to reject the restrictive model. Posterior predictive checking (PPC) provides an alternative approach to evaluating model-data discrepancy. This paper explores the utility of PPC in estimating measurement invariance. The simulation results show that the posterior predictive p (PP p) values of item parameter estimates respond to various invariance violations, whereas the PP p values of item-fit index may fail to detect such violations. The current paper suggests comparing group estimates and restrictive model estimates with posterior predictive distributions in order to demonstrate the pattern of misfit graphically.

This study investigated the effects of test length (10, 20 and 30 items), scoring schema (proportion of dichotomous ad polytomous scoring) and item analysis model (IRT and Rasch) on the ability estimates, test information levels and optimization criteria of mixed item format tests. Polytomous item responses to 30 items for 1000 examinees were simulated using the generalized partial-credit model and SAS software. Portions of the data were re-coded dichotomously over 11 structured proportions to create 33 sets of test responses including mixed item format tests. MULTILOG software was used to calculate the examinee ability estimates, standard errors, item and test information, reliability and fit indices. A comparison of IRT and Rasch item analysis procedures was made using SPSS software across ability estimates and standard errors of ability estimates using a 3 x 11 x 2 fixed factorial ANOVA. Effect sizes and power were reported for each procedure. Scheffe post hoc procedures were conducted on significant factos. Test information was analyzed and compared across the range of ability levels for all 66-design combinations. The results indicated that both test length and the proportion of items scored polytomously had a significant impact on the amount of test information produced by mixed item …

Effective utilization of instructional technology can provide a valuable method for the delivery of a school program, and enable a teacher to individualize according to student needs. Implementation of such a program is costly and requires careful planning and adequate staff development for school personnel. This study examined the degree of commitment by Texas school districts to the use of the latest technologies in their efforts to revolutionize education. Quantitative data were collected by using a survey that included five informational areas: (1) school district background, (2) funding for budget, (3) staff, (4) technology hardware, and (5) staff development. The study included 137 school districts representing the 5 University Interscholastic League (UIL) classifications (A through AAAAA). The survey was mailed to the school superintendents requesting that the persons most familiar with instructional technology be responsible for completing the questionnaires. Analysis of data examined the relationship between UIL classification and the amount of money expended on instructional technology. Correlation coefficients were determined between teachers receiving training in the use of technology and total personnel assigned to technology positions. Coefficients were calculated between a district providing a plan fortechnology and employment of a coordinator for instructional technology. Significance was established at the …

Short-to-medium projections were made of student semester credit hour enrollments for North Texas State University and the Texas Public and Senior Colleges and Universities (as defined by the Coordinating Board, Texas College and University System). Undergraduate, Graduate, Doctorate, Total, Education, Liberal Arts, and Business enrollments were projected. Fall + Spring, Fall, Summer I + Summer II, Summer I were time periods for which projections were made. A new regression analysis called "cycle regression" which employs nonlinear regression techniques to extract multifrequential phenomena from time-series data was employed for the analysis of the enrollment data. The heuristic steps employed in cycle regression analysis are similar to those used in fitting polynomial models. A trend line and one or more sin waves (cycles) are simultaneously estimated using a partial F test. The process of adding cycle(s) to the model continues until no more significant terms can be estimated.

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.

The present study examined the structural construct validity of the LoTi Digital-Age Survey, a measure of teacher instructional practices with technology in the classroom. Teacher responses (N = 2840) from across the United States were used to assess factor structure of the instrument using both exploratory and confirmatory analyses. Parallel analysis suggests retaining a five-factor solution compared to the MAP test that suggests retaining a three-factor solution. Both analyses (EFA and CFA) indicate that changes need to be made to the current factor structure of the survey. The last two factors were composed of items that did not cover or accurately measure the content of the latent trait. Problematic items, such as items with crossloadings, were discussed. Suggestions were provided to improve the factor structure, items, and scale of the survey.

This dissertation: (a) investigated the degree to which the squared canonical correlation coefficient is biased in multivariate nonnormal distributions and (b) identified formulae that adjust the squared canonical correlation coefficient (Rc2) such that it most closely approximates the true population effect under normal and nonnormal data conditions. Five conditions were manipulated in a fully-crossed design to determine the degree of bias associated with Rc2: distribution shape, variable sets, sample size to variable ratios, and within- and between-set correlations. Very few of the condition combinations produced acceptable amounts of bias in Rc2, but those that did were all found with first function results. The sample size to variable ratio (n:v)was determined to have the greatest impact on the bias associated with the Rc2 for the first, second, and third functions. The variable set condition also affected the accuracy of Rc2, but for the second and third functions only. The kurtosis levels of the marginal distributions (b2), and the between- and within-set correlations demonstrated little or no impact on the bias associated with Rc2. Therefore, it is recommended that researchers use n:v ratios of at least 10:1 in canonical analyses, although greater n:v ratios have the potential to produce even less bias. …