JMASM19: A SPSS Matrix For Determining Effect Sizes From Three Categories: r And Functions Of r, Differences Between Proportions, And Standardized Differences Between Means

The program is intended to provide editors, manuscript reviewers, students, and researchers with an SPSS matrix to determine an array of effect sizes not reported or the correctness of those reported, such as rrelated indices, r-related squared indices, and measures of association, when the only data provided in the manuscript or article are the n, M, and SD (and sometimes proportions and t and F (1) values) for twogroup designs. This program can create an internal matrix table to assist researchers in determining the size of an effect for commonly utilized r-related, mean difference, and difference in proportions indices when engaging in correlational and/or meta-analytic analyses

A Comparison of Eight Shrinkage Formulas under Extreme Conditions

The performance of various shrinkage formulas for estimating the population squared multiple correlation coefficient (ρ2) were compared under extreme conditions often found in educational research with small sample sizes of 10, 15, 20, 25, 30 and regressor variates ranging from 2 to 4. A new formula for estimating ρ2, Adj R2 DW, was examined in terms of its performance under various conditions of N, p, ρ2, along with its bias properties and standard error estimates. The two shrinkage formulas that performed most consistently were the Claudy (Adj R2 C) and Walker (Adj R2 DW

A Comparison of the Spearman-Brown and Flanagan-Rulon Formulas for Split Half Reliability under Various Variance Parameter Conditions

Differences between the Spearman-Brown and Flanagan-Rulon formulas are examined when the variance parameters for two halves of a test had the following ratios: 1.0, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2.0 and also had a correlation between the two halves of a test at 1.00, .95, .90, .80, .70, .60, .50, .40, .30, .20, .10, .05. It was found that use of the Spearman-Brown formula to estimate the population ρ when the ratio between the standard deviations on two halves of a test is disparate, or beyond .9 to 1.1, was not warranted. Applied and theoretical examples are employed, as well as syntax for user application

Estimating How Many Observations are Needed to Obtain a Required Level of Reliability

This article provides a detailed table containing estimations of how many observations are needed to obtain an increased reliability coefficient for situations such as observational data collection in the classroom. A SPSS program is provided for users to analyze situations where an initial reliability value is obtained and the user wants to determine how many more observations are needed to reach a required level of reliability

Validation Studies: Matters Of Dimensionality, Accuracy, And Parsimony With Predictive Discriminant Analysis And Factor Analysis

Two studies were used as examples that examined issues of dimensionality, accuracy, and parsimony in educational research via the use of predictive discriminant analysis and factor analysis. Using a two-group problem, study 1 looked at how accurately group membership could be predicted from subjects’ test scores. Study 2 looked at the dimensionality structure of an instrument and if it developed constructs that would measure theorized domains

Prairie Republic: The Political Culture of Dakota Territory, 1879–1889

Review of: Prairie Republic: The Political Culture of Dakota Territory, 1879–1889, by Jon K. Lauck

The Standard Error of a Proportion for Different Scores and Test Length

This paper examines Smith’s (2003) proposed standard error of a proportion index associated with the idea of reliability as sufficiency of information. A detailed table indexing all of the standard error values affiliated with assessments that range from 5 to 100 items, where students scored as low as 50% correct and 50% incorrect to as high as 95% correct and 5% incorrect, calculated in increments of 1 percentage point, is presented, along with distributional qualities. Examples using this measure for classroom teachers and higher education instructors of assessment are provided. Accessed 19,072 times on https://pareonline.net from June 05, 2005 to December 31, 2019. For downloads from January 1, 2020 forward, please click on the PlumX Metrics link to the right

Dear Brother: Letters of William Clark to Jonathan Clark

Review of: Dear Brother: Letters of William Clark to Jonathan Clark. Clark, William

JMASM 48: The Pearson Product-Moment Correlation Coefficient and Adjustment Indices: The Fisher Approximate Unbiased Estimator and the Olkin-Pratt Adjustment (SPSS)

This syntax program is intended to provide an application, not readily available, for users in SPSS who are interested in the Pearson product–moment correlation coefficient (r) and r biased adjustment indices such as the Fisher Approximate Unbiased estimator and the Olkin and Pratt adjustment