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Aydin, Burak; Leite, Walter L.; Algina, James – Educational and Psychological Measurement, 2016

We investigated methods of including covariates in two-level models for cluster randomized trials to increase power to detect the treatment effect. We compared multilevel models that included either an observed cluster mean or a latent cluster mean as a covariate, as well as the effect of including Level 1 deviation scores in the model. A Monte…

Descriptors: Error of Measurement, Predictor Variables, Randomized Controlled Trials, Experimental Groups

Algina, James; Keselman, H. J.; Penfield, Randall D. – Educational and Psychological Measurement, 2010

The increase in the squared multiple correlation coefficient ([delta]R[superscript 2]) associated with a variable in a regression equation is a commonly used measure of importance in regression analysis. Algina, Keselman, and Penfield found that intervals based on asymptotic principles were typically very inaccurate, even though the sample size…

Descriptors: Computation, Statistical Analysis, Correlation, Statistical Inference

Algina, James; Keselman, H. J. – Educational and Psychological Measurement, 2008

Applications of distribution theory for the squared multiple correlation coefficient and the squared cross-validation coefficient are reviewed, and computer programs for these applications are made available. The applications include confidence intervals, hypothesis testing, and sample size selection. (Contains 2 tables.)

Descriptors: Intervals, Sample Size, Validity, Hypothesis Testing

Algina, James; Keselman, Harvey J.; Penfield, Randall J. – Educational and Psychological Measurement, 2008

A squared semipartial correlation coefficient ([Delta]R[superscript 2]) is the increase in the squared multiple correlation coefficient that occurs when a predictor is added to a multiple regression model. Prior research has shown that coverage probability for a confidence interval constructed by using a modified percentile bootstrap method with…

Descriptors: Intervals, Correlation, Probability, Multiple Regression Analysis

Algina, James; Keselman, H. J.; Penfield, Randall D. – Educational and Psychological Measurement, 2007

The increase in the squared multiple correlation coefficient ([Delta]R[squared]) associated with a variable in a regression equation is a commonly used measure of importance in regression analysis. The coverage probability that an asymptotic and percentile bootstrap confidence interval includes [Delta][rho][squared] was investigated. As expected,…

Descriptors: Probability, Intervals, Multiple Regression Analysis, Correlation

Algina, James; Keselman, H. J.; Penfield, Randall D. – Educational and Psychological Measurement, 2006

Kelley compared three methods for setting a confidence interval (CI) around Cohen's standardized mean difference statistic: the noncentral-"t"-based, percentile (PERC) bootstrap, and biased-corrected and accelerated (BCA) bootstrap methods under three conditions of nonnormality, eight cases of sample size, and six cases of population…

Descriptors: Effect Size, Comparative Analysis, Sample Size, Investigations

Algina, James; Keselman, H. J.; Penfield, Randall D. – Educational and Psychological Measurement, 2005

Probability coverage for eight different confidence intervals (CIs) of measures of effect size (ES) in a two-level repeated measures design was investigated. The CIs and measures of ES differed with regard to whether they used least squares or robust estimates of central tendency and variability, whether the end critical points of the interval…

Descriptors: Probability, Intervals, Least Squares Statistics, Effect Size

Kowalchuk, Rhonda K.; Keselman, H. J.; Algina, James; Wolfinger, Russell D. – Educational and Psychological Measurement, 2004

One approach to the analysis of repeated measures data allows researchers to model the covariance structure of their data rather than presume a certain structure, as is the case with conventional univariate and multivariate test statistics. This mixed-model approach, available through SAS PROC MIXED, was compared to a Welch-James type statistic.…

Descriptors: Interaction, Sample Size, Statistical Analysis, Evaluation Methods

Peer reviewed

Algina, James; Keselman, H. J. – Educational and Psychological Measurement, 2003

Investigated the approximate confidence intervals for effect sizes developed by K. Bird (2002) and proposed a more accurate method developed through simulation studies. The average coverage probability for the new method was 0.959. (SLD)

Descriptors: Effect Size, Research Methodology, Simulation

Peer reviewed

Algina, James; Seaman, Samuel – Educational and Psychological Measurement, 1984

A simple formula for calculating semipartial correlations is presented and illustrated. (Author)

Descriptors: Correlation, Mathematical Formulas, Regression (Statistics)

Peer reviewed

Algina, James; Olejnik, Stephen F. – Educational and Psychological Measurement, 1984

The Welch-James procedure may be used to test hypothesis on means, when independent samples from populations with heterogenous variances are available. Summation formulas for the Welch-James procedure are presented for the 2x2 design. Matrix formulas that permit routine application of the procedure to crossed factorial designs are presented.…

Descriptors: Analysis of Variance, Hypothesis Testing, Mathematical Formulas, Matrices

Peer reviewed

Nthangeni, Mbulaheni; Algina, James – Educational and Psychological Measurement, 2001

Examined Type I error rates and power for four tests for treatment control studies in which a larger treatment mean may be accompanied by a larger treatment variance and examined these aspects of the independent samples "t" test and the Welch test. Evaluated each test and suggested conditions for the use of each approach. (SLD)

Descriptors: Control Groups, Power (Statistics), Research Design, Sampling

Peer reviewed

Algina, James; Hombo, Catherine M. – Educational and Psychological Measurement, 1998

The Statistical Analysis System (SAS) has been used to program power calculations for the independent samples Hotellings T squared. Three programs have been prepared to accommodate variations in the information that may be available to do the power analysis. (Author/SLD)

Descriptors: Computer Oriented Programs, Power (Statistics), Sampling

Peer reviewed

Coombs, William T.; Algina, James – Educational and Psychological Measurement, 1996

Univariate procedures proposed by M. Brown and A. Forsythe (1974) and the multivariate procedures from D. Nel and C. van der Merwe (1986) were generalized to form five new multivariate alternatives to one-way multivariate analysis of variance (MANOVA) for use when dispersion matrices are heteroscedastic. These alternatives are evaluated for Type I…

Descriptors: Analysis of Variance, Matrices, Multivariate Analysis

Peer reviewed

Algina, James – Educational and Psychological Measurement, 1998

In this study, the Statistical Analysis System (SAS) was used to program power calculations for multiple comparisons of two groups on "p" variables. Three programs were prepared to accommodate variations in the information that may be available to do the power analysis. (Author/SLD)

Descriptors: Comparative Analysis, Computer Software, Power (Statistics), Sample Size

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