Sampling error refers to variability that is unique to the sample. If the sample is the entire population, then there is no sampling error. A related point is that sampling error is a function of sample size, as a hypothetical example illustrates. As the sample statistics more and more closely approximate the population parameters, the sampling…

When analyzing open-ended or categorical questions, many times responses are cross-classified by other categorical variables. The resulting contingency tables are then analyzed using the chi square test of independence. This procedure leads to multiple significance tests and provides no method to assess higher order interactions. Loglinear…

The Welch-James (WJ) and Improved General Approximation (IGA) tests for the within-subjects main and interaction effects in a split-plot repeated measurement design were investigated when least squares estimates and robust estimates based on trimmed means were used. Variables manipulated in the Monte Carlo study included the degree of multivariate…

Repeated measures experimental designs, often referred to as "within-subjects" designs, offer researchers opportunities to study research effects while "controlling" for subjects. These designs offer greater statistical power relative to sample size. However, threats to internal validity such as carryover or practice effects…

This paper explains the underlying assumptions of the sampling distribution and its role in significance testing. To compute statistical significance, estimates of population parameters must be obtained so that only one sampling distribution is defined. A sampling distribution is the underlying distribution of a statistic. Sampling distributions…

Computer simulations under three conditions of polytomous differential item functioning (DIF) compared the ability of three different statistical procedures to detect nonuniform DIF. The procedures were a nominal and an ordinal extension of the Mantel-Haenszel statistic, and logistic discriminant function analysis. Results showed that only the…

The assumption of normality underlies much of the standard statistical methodology. Knowing how to determine whether a sample of measurements is from a normally distributed population is crucial both in the development of statistical theory and in practice. W. Ware and J. Ferron have developed a new test statistic, modeled after the K-squared test…

The benefits of item response theory (IRT) will only accrue to a testing program to the extent that model assumptions are met. Obtaining accurate item parameter estimates is a critical first step. However, the sample sizes required for stable parameter estimation are often difficult to obtain in practice, particularly for the more complex models.…

The purpose of this paper was to research published validity reports of the Multiple Assessment and Program Services (MAPS) Test and to conduct quantitative analysis on the validity coefficients from the MAPS reports to determine the generalizability of the results and to identify which variables in the reports impact these coefficients. The…

The Mantel-Haenszel (MH) procedure has become one of the most popular procedures for detecting differential item functioning. Valid results with relatively small numbers of examinees represent one of the advantages typically attributed to this procedure. In this study, examinee item responses were simulated to contain differentially functioning…

Several important issues related to canonical correlation have been recognized and resolved during the last several years. The purpose of this presentation is to offer an organized, comprehensive, and current annotated bibliography of the many recent developments and extensions of canonical methods. The bibliography does not emphasize references…

Methods to aid the statistical researchers in making arguments as to what constitutes minimal effect size (MES) are outlined. By selecting MES and determining power for that effect, the researcher communicates to the reader what the researcher considers to be important and what the researcher's chances are for finding that effect or a larger one.…

Evaluates arguments concerning the generality and statistical analysis of single-subject data. Considers the role of philosophy of science in evaluating research methodology. Single-subject data have special relevance for psychologists and educators who focus on the individual but statistical techniques for analyzing data have numerous…

In the process of fitting a quantitative synthesis model, the assumption of homogeneous effect size variation is assessed via omnibus test statistics. Graphical representations of data on techniques for teaching composition skills are used to help determine the extent to which sample estimates deviate from modeled population estimates. (TJH)

This paper describes how to determine whether enough observations have been sampled to be reasonably certain that a correct decision will be made about how the difference between the means of an experimental and control group compares to a constant specified by the experimenter. Equal variances are not assumed. (Author/BW)