共查询到20条相似文献，搜索用时 312 毫秒
1.
Jason A. Schoeneberger 《Journal of Experimental Education》2016,84(2):373-397
The design of research studies utilizing binary multilevel models must necessarily incorporate knowledge of multiple factors, including estimation method, variance component size, or number of predictors, in addition to sample sizes. This Monte Carlo study examined the performance of random effect binary outcome multilevel models under varying methods of estimation, level-1 and level-2 sample size, outcome prevalence, variance component sizes, and number of predictors using SAS software. Mean estimates of statistical power were influenced primarily by sample sizes at both levels. In addition, confidence interval coverage and width and the likelihood of nonpositive definite random effect covariance matrices were impacted by variance component size and estimation method. The interactions of these and other factors with various model performance outcomes are explored. 相似文献
2.
Tzu-Yao Lin 《Structural equation modeling》2013,20(3):482-490
Kelley and Lai (2011) recently proposed the use of accuracy in parameter estimation (AIPE) for sample size planning in structural equation modeling. The sample size that reaches the desired width for the confidence interval of root mean square error of approximation (RMSEA) is suggested. This study proposes a graphical extension with the AIPE approach, abbreviated as GAIPE, on RMSEA to facilitate sample size planning in structural equation modeling. GAIPE simultaneously displays the expected width of a confidence interval of RMSEA, the necessary sample size to reach the desired width, and the RMSEA values covered in the confidence interval. Power analysis for hypothesis tests related to RMSEA can also be integrated into the GAIPE framework to allow for a concurrent consideration of accuracy in estimation and statistical power to plan sample sizes. A package written in R has been developed to implement GAIPE. Examples and instructions for using the GAIPE package are presented to help readers make use of this flexible framework. With the capacity of incorporating information on accuracy in RMSEA estimation, values of RMSEA, and power for hypothesis testing on RMSEA in a single graphical representation, the GAIPE extension offers an informative and practical approach for sample size planning in structural equation modeling. 相似文献
3.
Robert S. Barcikowski 《Journal of Experimental Education》2013,81(4):10-16
In most behavioral science research very little attention is ever given to the probability of committing a Type II error, i.e., the probability of failing to reject a false null hypothesis. Recent publications by Cohen (2, 3) have led to a great deal of insight on this topic for the fixed-effects analysis of variance and covariance. These publications should prove invaluable in aiding social scientists to carry out and better understand their research. It is the purpose of this paper to provide social scientists with some insight in dealing with Type II error, and therefore, optimum sample size and number of levels, in the random-effects analysis of variance. 相似文献
4.
This study examined the effect of sample size ratio and model misfit on the Type I error rates and power of the Difficulty Parameter Differences procedure using Winsteps. A unidimensional 30-item test with responses from 130,000 examinees was simulated and four independent variables were manipulated: sample size ratio (20/100/250/500/1000); model fit/misfit (1 PL and 3PLc =. 15 models); impact (no difference/mean differences/variance differences/mean and variance differences); and percentage of items with uniform and nonuniform DIF (0%/10%/20%). In general, the results indicate the importance of ensuring model fit to achieve greater control of Type I error and adequate statistical power. The manipulated variables produced inflated Type I error rates, which were well controlled when a measure of DIF magnitude was applied. Sample size ratio also had an effect on the power of the procedure. The paper discusses the practical implications of these results. 相似文献
5.
This study presents a new approach to synthesizing differential item functioning (DIF) effect size: First, using correlation matrices from each study, we perform a multigroup confirmatory factor analysis (MGCFA) that examines measurement invariance of a test item between two subgroups (i.e., focal and reference groups). Then we synthesize, across the studies, the differences in the estimated factor loadings between the two subgroups, resulting in a meta-analytic summary of the MGCFA effect sizes (MGCFA-ES). The performance of this new approach was examined using a Monte Carlo simulation, where we created 108 conditions by four factors: (1) three levels of item difficulty, (2) four magnitudes of DIF, (3) three levels of sample size, and (4) three types of correlation matrix (tetrachoric, adjusted Pearson, and Pearson). Results indicate that when MGCFA is fitted to tetrachoric correlation matrices, the meta-analytic summary of the MGCFA-ES performed best in terms of bias and mean square error values, 95% confidence interval coverages, empirical standard errors, Type I error rates, and statistical power; and reasonably well with adjusted Pearson correlation matrices. In addition, when tetrachoric correlation matrices are used, a meta-analytic summary of the MGCFA-ES performed well, particularly, under the condition that a high difficulty item with a large DIF was administered to a large sample size. Our result offers an option for synthesizing the magnitude of DIF on a flagged item across studies in practice. 相似文献
6.
《The Journal of educational research》2012,105(5):309-326
ABSTRACT This randomized control trial study evaluated the effectiveness of the solution-focused approach in addressing academic, motivational, and socioemotional needs of 14 children with reading difficulties. The intervention group received five 40-min solution-focused sessions. The control group received academic homework support. Results showed advantages for the intervention condition in 26 out of 38 measures. The mean eta-squared effect size for intervention was .20 (very) large. For the control group, there were only 10 effects favoring it and the mean was .09, a medium sized effect, both significantly greater than 0 (p < .01). Comparisons of the solution-focused brief therapy (SFBT) effect sizes to the mean of the control showed it was significantly larger (p < .001), confirming that SFBT was an efficacious intervention in this sample. 相似文献
7.
William J. Moonan 《Journal of Experimental Education》2013,81(3):285-288
When no dedicated weighted least-squares procedure is available, misapplying a case-weighting strategy as a method of implementing a weighted least-squares regression analysis can lead to gross inaccuracies. The magnitudes of many of the obtained estimates depend strongly on the absolute magnitudes of the weights applied during fitting and, in addition, several of the crucial regression estimates are incorrect. Among all possible rescalings, the most successful weights are those that have been rescaled so that they sum to the original sample size. However, even with the application of these rescaled weights, the estimation of the error (residual) variance continues to be incorrect. A simple and easily applied adjustment to rectify this problem is presented. 相似文献
8.
The goal of the study was to examine the association between visual‐attentional span and lexical decision in skilled adult readers. In the span tasks, an array of letters was presented briefly and recognition or production of a single cued letter (partial span) or production of all letters (whole span) was required. Independently of letter recognition and phoneme awareness, width of partial recognition span predicted substantial variance only in detection of letter misorderings in words, while partial span efficiency made small contributions to decisions on regular words and pseudowords, but not strange words. With a production format and the inclusion of short‐term phonological memory, neither partial‐span nor whole‐span measures contributed positive independent variance to word and nonword decisions. The results provide meagre support for the idea that skilled adult readers with a wide visual‐attentional span might process words more effectively than those with a narrow span during lexical decision. 相似文献
9.
Alice Sowers 《Journal of Experimental Education》2013,81(2):205-232
The authors examined the distributional properties of 3 improvement-over-chance, I, effect sizes each derived from linear and quadratic predictive discriminant analysis and from logistic regression analysis for the 2-group univariate classification. These 3 classification methods (3 levels) were studied under varying levels of data conditions, including population separation (3 levels), variance pattern (3 levels), total sample size (3 levels), and prior probabilities (5 levels). The results indicated that the decision of which effect size to choose is primarily determined by the variance pattern and prior probabilities. Some of the I indices performed well for some small sample cases and quadratic predictive discriminant analysis I tended to work well with extreme variance heterogeneity and differing prior probabilities. 相似文献
10.
Youngsuk Suh 《Journal of Educational Measurement》2016,53(4):403-430
This study adapted an effect size measure used for studying differential item functioning (DIF) in unidimensional tests and extended the measure to multidimensional tests. Two effect size measures were considered in a multidimensional item response theory model: signed weighted P‐difference and unsigned weighted P‐difference. The performance of the effect size measures was investigated under various simulation conditions including different sample sizes and DIF magnitudes. As another way of studying DIF, the χ2 difference test was included to compare the result of statistical significance (statistical tests) with that of practical significance (effect size measures). The adequacy of existing effect size criteria used in unidimensional tests was also evaluated. Both effect size measures worked well in estimating true effect sizes, identifying DIF types, and classifying effect size categories. Finally, a real data analysis was conducted to support the simulation results. 相似文献
11.
We examine the power associated with the test of factor mean differences when the assumption of factorial invariance is violated. Utilizing the Wald test for obtaining power, issues of model size, sample size, and total versus partial noninvariance are considered along with variation of actual factor mean differences. Results of a population study show that power is profoundly affected by true factor mean differences but is relatively unaffected by the degree of factor loading noninvariance. Inequality of sample size has a profound effect on power probabilities with power decreasing as sample sizes become increasingly disparate. Sample size variations operate such that power is uniformly lower when the group with the smaller generalized variance is associated with the smaller sample size. An increase in the number of variables yields uniformly larger power probabilities. No substantial differences are found between total and partial noninvariance. Results are related to work in the area of robustness of Hotelling's T 2 statistic and discussed in terms of asymptotic covariability of factor means and factor loadings. Implications for practice are considered. 相似文献
12.
The log-odds ratio (ln[OR]) is commonly used to quantify treatments' effects on dichotomous outcomes and then pooled across studies using inverse-variance (1/v) weights. Calculation of the ln[OR]'s variance requires four cell frequencies for two groups crossed with values for dichotomous outcomes. While primary studies report the total sample size (n..), many do not report all four frequencies. Using real data, we demonstrated pooling of ln[OR]s using n.. versus 1/v weights. In a simulation study we compared two weighting approaches under several conditions. Efficiency and Type I error rates for 1/v versus n.. weights used to pool ln[OR] estimates depended on sample size and the percent of studies missing cell frequencies. Results are discussed and guidelines for applied meta-analysts are provided. 相似文献
13.
This article discusses the sample size requirements for the interaction, row, and column effects, respectively, by forming a linear contrast for a 2×2 factorial design for fixed-effects heterogeneous analysis of variance. The proposed method uses the Welch t test and its corresponding degrees of freedom to calculate the final sample size in a 2-step procedure. The simulation results show that the proposed sample size allocation ratio can minimize the sampling cost, while at the same time the designated power is achieved. The article concludes with a discussion to reiterate the importance of sample size planning, especially for testing the iteration effect. 相似文献
14.
Dexin Shi Christine DiStefano Heather L. McDaniel Zhehan Jiang 《Structural equation modeling》2018,25(6):924-945
This study examined the effect of model size on the chi-square test statistics obtained from ordinal factor analysis models. The performance of six robust chi-square test statistics were compared across various conditions, including number of observed variables (p), number of factors, sample size, model (mis)specification, number of categories, and threshold distribution. Results showed that the unweighted least squares (ULS) robust chi-square statistics generally outperform the diagonally weighted least squares (DWLS) robust chi-square statistics. The ULSM estimator performed the best overall. However, when fitting ordinal factor analysis models with a large number of observed variables and small sample size, the ULSM-based chi-square tests may yield empirical variances that are noticeably larger than the theoretical values and inflated Type I error rates. On the other hand, when the number of observed variables is very large, the mean- and variance-corrected chi-square test statistics (e.g., based on ULSMV and WLSMV) could produce empirical variances conspicuously smaller than the theoretical values and Type I error rates lower than the nominal level, and demonstrate lower power rates to reject misspecified models. Recommendations for applied researchers and future empirical studies involving large models are provided. 相似文献
15.
We compared six common methods in estimating the 2-1-1 (level-2 independent, level-1 mediator, level-1 dependent) multilevel mediation model with a random slope. They were the Bayesian with informative priors, the Bayesian with non-informative priors, the Monte-Carlo, the distribution of the product, the bias-corrected, and the bias-uncorrected parametric percentile residual bootstrap. The Bayesian method with informative priors was superior in relative mean square error (RMSE), power, interval width, and interval imbalance. The prior variance and prior mean were also varied and examined. Decreasing the prior variance increased the power, reduced RMSE and interval width when the prior mean was the true value, but decreasing the prior variance reduced the power when the prior mean was set incorrectly. The influence of misspecification of prior information of the b coefficient on multilevel mediation analysis was greater than that on coefficient a. An illustrate example with the Bayesian multilevel mediation was provided. 相似文献
16.
《教育实用测度》2013,26(4):329-349
The logistic regression (LR) procedure for differential item functioning (DIF) detection is a model-based approach designed to identify both uniform and nonuniform DIF. However, this procedure tends to produce inflated Type I errors. This outcome is problematic because it can result in the inefficient use of testing resources, and it may interfere with the study of the underlying causes of DIF. Recently, an effect size measure was developed for the LR DIF procedure and a classification method was proposed. However, the effect size measure and classification method have not been systematically investigated. In this study, we developed a new classification method based on those established for the Simultaneous Item Bias Test. A simulation study also was conducted to determine if the effect size measure affects the Type I error and power rates for the LR DIF procedure across sample sizes, ability distributions, and percentage of DIF items included on a test. The results indicate that the inclusion of the effect size measure can substantially reduce Type I error rates when large sample sizes are used, although there is also a reduction in power. 相似文献
17.
通过对激光粒度分析仪测量硅钢级氧化镁（MgO）的分析条件进行优化,如分散介质、分散方式、样品预处理、仪器暗淡度等,探讨了硅钢级MgO粒度范围测量重现性较好的试验方法,满足硅钢生产过程控制对MgO粒度的要求。 相似文献
18.
CSCL研究中常需要处理小组变量和学习者个体变量两种数据,而个体嵌套在小组中,形成两层结构数据。传统的方差分析或线性回归模型仅能针对单层数据,处理多层数据时,易出现标准误差偏移,影响分析的可信度。多层线性建模尽管受CSCL领域样本数的限制,在组层次可能产生偏移量,但能处理稀疏数据,能比较、评估不同层次变异对总变异的贡献度,确定不同层次变量对因变量的影响程度,反映因变量测量随时间变化的发展轨迹,是CSCL领域比较合适的研究方法。 相似文献
19.
This article presents 3 standardized effect size measures to use when sharing results of an analysis of mediation of treatment effects for cluster-randomized trials. The authors discuss 3 examples of mediation analysis (upper-level mediation, cross-level mediation, and cross-level mediation with a contextual effect) with demonstration of the calculation and interpretation of the effect size measures using a simulated dataset and an empirical dataset from a cluster-randomized trial of peer tutoring. SAS syntax is provided for parametric percentile bootstrapped confidence intervals of the effect sizes. The use of any of the 3 standardized effect size measures depends on the nature of the inference the researcher wishes to make within a single site, across the broad population, or at the site level. 相似文献
20.