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Social and Behavioral Sciences Commons™
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- Effect size (5)
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Articles 31 - 55 of 55
Full-Text Articles in Social and Behavioral Sciences
Fast Permutation Tests That Maximize Power Under Conventional Monte Carlo Sampling For Pairwise And Multiple Comparisons, J. D. Opdyke
Fast Permutation Tests That Maximize Power Under Conventional Monte Carlo Sampling For Pairwise And Multiple Comparisons, J. D. Opdyke
Journal of Modern Applied Statistical Methods
While the distribution-free nature of permutation tests makes them the most appropriate method for hypothesis testing under a wide range of conditions, their computational demands can be runtime prohibitive, especially if samples are not very small and/or many tests must be conducted (e.g. all pairwise comparisons). This paper presents statistical code that performs continuous-data permutation tests under such conditions very quickly often more than an order of magnitude faster than widely available commercial alternatives when many tests must be performed and some of the sample pairs contain a large sample. Also presented is an efficient method for obtaining a …
Analyzing Group By Time Effects In Longitudinal Two-Group Randomized Trial Designs With Missing Data, James Algina, H. J. Keselman, Abdul R. Othman
Analyzing Group By Time Effects In Longitudinal Two-Group Randomized Trial Designs With Missing Data, James Algina, H. J. Keselman, Abdul R. Othman
Journal of Modern Applied Statistical Methods
We investigated bias, sampling variability, Type I error and power of nine approaches for testing the group by time interaction in a repeated measures design under three types of missing data mechanisms. One procedure due to Overall, Ahn, Shivakumar, and Kalburgi (1999) performed reasonably well over a range of conditions.
A Parametric Bootstrap Version Of Hedges’ Homogeneity Test, Wim Van Den Noortgate, Patrick Onghena
A Parametric Bootstrap Version Of Hedges’ Homogeneity Test, Wim Van Den Noortgate, Patrick Onghena
Journal of Modern Applied Statistical Methods
Hedges’ Q-test is frequently used in meta-analyses to evaluate the homogeneity of effect sizes, but for several kinds of effect size measures it does not always appropriately control the Type 1 error probability. Therefore we propose a parametric bootstrap version, which shows Type 1 error control under a broad set of circumstances. This is confirmed in a small simulation study.
Randomization Technique, Allocation Concealment, Masking, And Susceptibility Of Trials To Selection Bias, Vance W. Berger, Costas A. Christophi
Randomization Technique, Allocation Concealment, Masking, And Susceptibility Of Trials To Selection Bias, Vance W. Berger, Costas A. Christophi
Journal of Modern Applied Statistical Methods
It is widely believed that baseline imbalances in randomized clinical trials must necessarily be random. Yet even among masked randomized trials conducted with allocation concealment, there are mechanisms by which patients with specific covariates may be selected for inclusion into a particular treatment group. This selection bias would force imbalance in those covariates, measured or unmeasured, that are used for the patient selection. Unfortunately, few trials provide adequate information to determine even if there was allocation concealment, how the randomization was conducted, and how successful the masking may have been, let alone if selection bias was adequately controlle d. In …
Screening Properties And Design Selection Of Certain Two-Level Designs, H. Evangelaras, Christos Koukouvinos
Screening Properties And Design Selection Of Certain Two-Level Designs, H. Evangelaras, Christos Koukouvinos
Journal of Modern Applied Statistical Methods
Screening designs are useful for situations where a large number of factors (q) is examined but only few (k) of these are expected to be important. It is of practical interest for a given k to know all the inequivalent projections of the design into the k dimensions. In this paper we give all the inequivalent projections of inequivalent Hadamard matrices of order 28 into k=3 and 4 dimensions and furthermore, we give partial results for k=5. Then, we sort these projections according to their generalized resolution and their generalized aberration.
Performing Two-Way Analysis Of Variance Under Variance Heterogeneity, Scott J. Richter, Mark E. Payton
Performing Two-Way Analysis Of Variance Under Variance Heterogeneity, Scott J. Richter, Mark E. Payton
Journal of Modern Applied Statistical Methods
Small sample properties of the method proposed by Brunner et al. (1997) for performing two-way analysis of variance are compared to those of the normal based ANOVA method for factorial arrangements. Different effect sizes, sample sizes, and error structures are utilized in a simulation study to compare type I error rates and power of the two methods. An SAS program is also presented to assist those wishing to implement the Brunner method to real data.
Without Supporting Statistical Evidence, Where Would Reported Measures Of Substantive Importance Lead? To No Good Effect, Anthony J. Onwuegbuzie, Joel R. Levin
Without Supporting Statistical Evidence, Where Would Reported Measures Of Substantive Importance Lead? To No Good Effect, Anthony J. Onwuegbuzie, Joel R. Levin
Journal of Modern Applied Statistical Methods
Although estimating substantive importance (in the form of reporting effect sizes) has recently received widespread endorsement, its use has not been subjected to the same degree of scrutiny as has statistical hypothesis testing. As such, many researchers do not seem to be aware that certain of the same criticisms launched against the latter can also be aimed at the former. Our purpose here is to highlight major concerns about effect sizes and their estimation. In so doing, we argue that effect size measures per se are not the hoped-for panaceas for interpreting empirical research findings. Further, we contend that if …
Using Multinomial Logistic Models To Predict Adolescent Behavioral Risk, Chao-Ying Joanne Peng, Rebecca Naegle Nichols
Using Multinomial Logistic Models To Predict Adolescent Behavioral Risk, Chao-Ying Joanne Peng, Rebecca Naegle Nichols
Journal of Modern Applied Statistical Methods
Multinomial logistic regression was applied to data comprising 432 adolescents’ self reports of engagement in risky behaviors. Results showed that gender, intention to drop from the school, family structure, self-esteem, and emotional risk were effective predictors collectively. Three methodological issues were highlighted: (1) the use of odds ratio, (2) the absence of an extension of the Hosmer and Lemeshow test for multinomial logistic models, and (3) the missing data problem. Psychologists and educators can utilize findings to plan prevention programs, as well as to apply the versatile and effective logistic technique in psychological, educational, and health research concerning adolescents.
Bayesian Analysis Of Poverty Rates: The Case Of Vietnamese Provinces, Dominique Haughton, Nguyen Phong
Bayesian Analysis Of Poverty Rates: The Case Of Vietnamese Provinces, Dominique Haughton, Nguyen Phong
Journal of Modern Applied Statistical Methods
This paper presents a Bayesian analysis of poverty rates in urban Ho Chi Minh City and rural Nghe An province in Vietnam. Using mixtures of beta distributions as priors for the poverty rates, we find that, when the prior is reasonably informative, our approach yields more accurate estimated poverty rates than a frequentist approach. On the other hand, we find that, in the presence of poor/non-poor misclassification, average probabilities of posterior credible intervals for poverty rates can fall well short of .95 even with sample sizes such as 2000 or 3000 when the width of the interval is for example …
Comparison Of Estimates Of Proprietary And Syndicated Methods In Auto Industry Surveys, Daniel X. Wang
Comparison Of Estimates Of Proprietary And Syndicated Methods In Auto Industry Surveys, Daniel X. Wang
Journal of Modern Applied Statistical Methods
Proprietary and syndicate surveys are often used in assessing appeal and initial quality of new vehicles for automobile manufactures. This study discusses the difference between the two types of studies, and proposes a computer simulation based method for checking the appropriateness of the comparisons.
Steady State Analysis Of An M/D/2 Queue With Bernoulli Schedule Server Vacations, Kailash C. Madan, Walid Abu-Dayyeh, Firas Tayyan
Steady State Analysis Of An M/D/2 Queue With Bernoulli Schedule Server Vacations, Kailash C. Madan, Walid Abu-Dayyeh, Firas Tayyan
Journal of Modern Applied Statistical Methods
We examine an M/D/2 queue with Bernoulli schedules and a single vacation policy. We have assumed Poisson arrivals waiting in a single queue and two parallel servers who provide identical deterministic service to customers on first-come, first-served basis. We consider two models; in one we assume that after completion of a service both servers can take a vacation while in the other we assume that only one may take a vacation. The vacation periods in both models are assumed to be exponential. We obtain steady state probability generating functions of system size for various states of the servers.
Not All Effects Are Created Equal: A Rejoinder To Sawilowsky, J. Kyle Roberts, Robin K. Henson
Not All Effects Are Created Equal: A Rejoinder To Sawilowsky, J. Kyle Roberts, Robin K. Henson
Journal of Modern Applied Statistical Methods
In the continuing debate over the use and utility of effect sizes, more discussion often helps to both clarify and syncretize methodological views. Here, further defense is given of Roberts & Henson (2002) in terms of measuring bias in Cohen’s d, and a rejoinder to Sawilowsky (2003) is presented.
Trivials: The Birth, Sale, And Final Production Of Meta-Analysis, Shlomo S. Sawilowsky
Trivials: The Birth, Sale, And Final Production Of Meta-Analysis, Shlomo S. Sawilowsky
Journal of Modern Applied Statistical Methods
The structure of the first invited debate in JMASM is to present a target article (Sawilowsky, 2003), provide an opportunity for a response (Roberts & Henson, 2003), and to follow with independent comments from noted scholars in the field (Knapp, 2003; Levin & Robinson, 2003). In this rejoinder, I provide a correction and a clarification in an effort to bring some closure to the debate. The intension, however, is not to rehash previously made points, even where I disagree with the response of Roberts & Henson (2003).
Was Monte Carlo Necessary?, Thomas R. Knapp
Was Monte Carlo Necessary?, Thomas R. Knapp
Journal of Modern Applied Statistical Methods
In the critique that follows, I have attempted to summarize the principal disagreements between Sawilowsky and Roberts & Henson regarding the reporting and interpreting of statistically non-significant effect sizes, and to provide my own personal evaluations of their respective arguments.
Improved Multiple Comparisons With The Best In Response Surface Methodology, Laura K. Miller, Ping Sa
Improved Multiple Comparisons With The Best In Response Surface Methodology, Laura K. Miller, Ping Sa
Journal of Modern Applied Statistical Methods
A method to construct simultaneous confidence intervals about the difference in mean responses at the stationary point and at x for all x within a sphere with radius I R is proposed. Results of an efficiency study to compare the new method and the existing method by Moore and Sa (1999) are provided.
The Trouble With Interpreting Statistically Nonsignificant Effect Sizes In Single-Study Investigations, Joel R. Levin, Daniel H. Robinson
The Trouble With Interpreting Statistically Nonsignificant Effect Sizes In Single-Study Investigations, Joel R. Levin, Daniel H. Robinson
Journal of Modern Applied Statistical Methods
In this commentary, we offer a perspective on the problem of authors reporting and interpreting effect sizes in the absence of formal statistical tests of their chanceness. The perspective reinforces our previous distinction between single-study investigations and multiple-study syntheses.
A Different Future For Social And Behavioral Science Research, Shlomo S. Sawilowsky
A Different Future For Social And Behavioral Science Research, Shlomo S. Sawilowsky
Journal of Modern Applied Statistical Methods
The dissemination of intervention and treatment outcomes as effect sizes bounded by conf idence intervals in order to think meta-analytically was promoted in a recent article in Educational Researcher. I raise concerns with unfettered reporting of effect sizes, point out the con in confidence interval, and caution against thinking meta-analytically. Instead, cataloging effect sizes is recommended for sample size estimation and power analysis to improve social and behavioral science research.
Jmasm6: An Algorithm For Generating Exact Critical Values For The Kruskal-Wallis One-Way Anova, Todd C. Headrick
Jmasm6: An Algorithm For Generating Exact Critical Values For The Kruskal-Wallis One-Way Anova, Todd C. Headrick
Journal of Modern Applied Statistical Methods
A Fortran 77 subroutine is provided for computing exact critical values for the Kruskal-Wallis test on k independent groups with equal or unequal samples sizes. The subroutine requires the user to provide sorting and ranking routines and a uniform pseudo-random number generator. The program is available from the author on request.
A Recursive Algorithm For Fractionally Differencing Long Data Series, Joseph Mccarthy, Robert Disario, Hakan Saraoglu
A Recursive Algorithm For Fractionally Differencing Long Data Series, Joseph Mccarthy, Robert Disario, Hakan Saraoglu
Journal of Modern Applied Statistical Methods
We propose a recursive algorithm to fractionally difference time series data. The algorithm eliminates the need to evaluate the gamma function directly, and hence avoids the overflow problem that arises when fractionally differencing a long data series. The proposed algorithm can be implemented using any general matrix programming language. An implementation using SAS is presented. The algorithm and the code provide a practical approach to including fractional differencing as part of a time series data analysis.
Modeling Correlated Time-Varying Covariate Effects In A Cox-Type Regression Model, Mourad Tighiouart
Modeling Correlated Time-Varying Covariate Effects In A Cox-Type Regression Model, Mourad Tighiouart
Journal of Modern Applied Statistical Methods
In this paper, I extend the proposed model by McKeague and Tighiouart (2000) to handle time-varying correlated covariate effects for the analysis of survival data. I use the conditional predictive ordinates (CPO’s) for model comparison and the methodology is illustrated by an application to nasopharynx cancer survival data. A reversible jump MCMC sampler to estimate the CPO’s will be presented.
Incorporating Sampling Weights Into The Generalizability Theory For Large-Scale Analyses, Christopher W. T. Chiu, Ronald S. Fesco
Incorporating Sampling Weights Into The Generalizability Theory For Large-Scale Analyses, Christopher W. T. Chiu, Ronald S. Fesco
Journal of Modern Applied Statistical Methods
Large scale studies frequently use complex sampling procedures, disproportionate sampling weights, and adjustment techniques to account for potential bias due to nonresponses and to ensure that results from the sample can be generalized to a larger population. Survey researchers are concerned about measurement error and the use of weights in developing models. Consequently, multiple weighting factors are used and these weighting factors are manifested as a final survey (composite) weight available for analysis. We developed a method to incorporate an external weighting factor like this for analyses of measurement errors in the theory of generalizability to provide researchers with a …
A More Efficient Way Of Obtaining A Unique Median Estimate For Circular Data, B. Sango Otieno, Christine M. Anderson-Cook
A More Efficient Way Of Obtaining A Unique Median Estimate For Circular Data, B. Sango Otieno, Christine M. Anderson-Cook
Journal of Modern Applied Statistical Methods
The procedure for computing the sample circular median occasionally leads to a non-unique estimate of the population circular median, since there can sometimes be two or more diameters that divide data equally and have the same circular mean deviation. A modification in the computation of the sample median is suggested, which not only eliminates this non-uniqueness problem, but is computationally easier and faster to work with than the existing alternative.
A Semiparametric Regression Model For Oligonucleotide Arrays, Jianhua Hu, Guosheng Yin
A Semiparametric Regression Model For Oligonucleotide Arrays, Jianhua Hu, Guosheng Yin
Journal of Modern Applied Statistical Methods
A semiparametric model incorporating the spline smoothing technique is proposed to study oligonucleotide gene expression data. No specific parametric functional form is assumed for mismatch probe intensities, which allows much more flexibility in the fitted model. The new approach improves the model fitting, hence the estimation of expression indexes. The method is applied to a data set of 18 HuGeneFL arrays.
The Way Ahead In Qualitative Computing, Tom Richards, Lyn Richards
The Way Ahead In Qualitative Computing, Tom Richards, Lyn Richards
Journal of Modern Applied Statistical Methods
Specialized computer programs for Qualitative Research in social sciences have greatly changed ways of doing QR, the reliability and comprehensiveness of results, the ability to inspect and challenge a researcher’s working, and the relationship with quantitative methods in social research. This article explores these claims in the context of N6 (NUD*IST) and NVivo, the two programs designed by the authors; and considers possible future developments in the field.
Homogeneous Markov Processes For Breast Cancer Analysis, Ricardo Ocaña-Rilola, Emilio Sanchez-Cantalejo, Carmen Martinez-Garcia
Homogeneous Markov Processes For Breast Cancer Analysis, Ricardo Ocaña-Rilola, Emilio Sanchez-Cantalejo, Carmen Martinez-Garcia
Journal of Modern Applied Statistical Methods
Sometimes, the introduction of covariates in stochastic processes is required to study their effect on disease history events. However these types of models increase the complexity of analysis, even for simpler processes, and standard software to analyse stochastic processes is limited. In this paper, a method for fitting homogeneous Markov models with covariates is proposed for analysing breast cancer data. Specific software for this purpose has been implemented.