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1.
Differential Item Functioning (DIF) is traditionally used to identify different item performance patterns between intact groups, most commonly involving race or sex comparisons. This study advocates expanding the utility of DIF as a step in construct validation. Rather than grouping examinees based on cultural differences, the reference and focal groups are chosen from two extremes along a distinct cognitive dimension that is hypothesized to supplement the dominant latent trait being measured. Specifically, this study investigates DIF between proficient and non-proficient fourth- and seventh-grade writers on open-ended mathematics test items that require students to communicate about mathematics. It is suggested that the occurrence of DIF in this situation actually enhances, rather than detracts from, the construct validity of the test because, according to the National Council of Teachers of Mathematics (NCTM), mathematical communication is an important component of mathematical ability, the dominant construct being assessed. However, the presence of DIF influences the validity of inferences that can be made from test scores and suggests that two scores should be reported, one for general mathematical ability and one for mathematical communication. The fact that currently only one test score is reported, a simple composite of scores on multiple-choice and open-ended items, may lead to incorrect decisions being made about examinees. 相似文献
2.
Mariola Moeyaert Maaike Ugille John M. Ferron S. Natasha Beretvas Wim Van den Noortgate 《Journal of Experimental Education》2016,84(3):473-509
The impact of misspecifying covariance matrices at the second and third levels of the three-level model is evaluated. Results indicate that ignoring existing covariance has no effect on the treatment effect estimate. In addition, the between-case variance estimates are unbiased when covariance is either modeled or ignored. If the research interest lies in the between-study variance estimate, including at least 30 studies is warranted. Modeling covariance does not result in less biased between-study variance estimates as the between-study covariance estimate is biased. When the research interest lies in the between-case covariance, the model including covariance results in unbiased between-case variance estimates. The three-level model appears to be less appropriate for estimating between-study variance if fewer than 30 studies are included. 相似文献
3.
This study examines the use of cross-classified random effects models (CCrem) and cross-classified multiple membership random effects models (CCMMrem) to model rater bias and estimate teacher effectiveness. Effect estimates are compared using CTT versus item response theory (IRT) scaling methods and three models (i.e., conventional multilevel model, CCrem, CCMMrem). Results indicate that ignoring rater bias can lead to teachers being misclassified within an evaluation system. The best estimates of teacher effectiveness are produced using CCrems regardless of scaling method. Use of CCMMrems to model rater bias cannot be recommended based on the results of this study; combining the use of CCMMrems with an IRT scaling method produced especially unstable results. 相似文献
4.
Beginning literacy: links among teacher knowledge, teacher practice, and student learning 总被引：2，自引：0，他引：2
McCutchen D Abbott RD Green LB Beretvas SN Cox S Potter NS Quiroga T Gray AL 《Journal of learning disabilities》2002,35(1):69-86
Although the importance of phonological awareness has been discussed widely in the research literature, the concept is not well understood by many classroom teachers. In the study described here, we worked with groups of kindergarten and first-grade teachers (the experimental group) during a 2-week summer institute and throughout the school year. We shared with them research about learning disabilities and effective instruction, stressing the importance of explicit instruction in phonological and orthographic awareness. We followed the experimental group and a control group into their classrooms for a year, assessing teachers' classroom practices and their students' (n = 779) learning. The study yielded three major findings: We can deepen teachers' own knowledge of the role of phonological and orthographic information in literacy instruction; teachers can use that knowledge to change classroom practice; and changes in teacher knowledge and classroom practice can improve student learning. 相似文献
5.
Eunkyeng Baek S. Natasha Beretvas Wim Van den Noortgate John M. Ferron 《Journal of Experimental Education》2020,88(4):698-710
AbstractRecently, researchers have used multilevel models for estimating intervention effects in single-case experiments that include replications across participants (e.g., multiple baseline designs) or for combining results across multiple single-case studies. Researchers estimating these multilevel models have primarily relied on restricted maximum likelihood (REML) techniques, but Bayesian approaches have also been suggested. The purpose of this Monte Carlo simulation study was to examine the impact of estimation method (REML versus Bayesian with noninformative priors) on the estimation of treatment effects (relative bias, root mean square error) and on the inferences about those effects (interval coverage) for autocorrelated multiple-baseline data. Simulated conditions varied with regard to the number of participants, series length, and distribution of the variance within and across participants. REML and Bayesian estimation led to estimates of the fixed effects that showed little to no bias but that differentially impacted the inferences about the fixed effects and the estimates of the variances. Implications for applied researchers and methodologists are discussed. 相似文献
6.
Maaike Ugille Mariola Moeyaert S. Natasha Beretvas John M. Ferron Wim Van den Noortgate 《Journal of Experimental Education》2013,81(3):358-374
A multilevel meta-analysis can combine the results of several single-subject experimental design studies. However, the estimated effects are biased if the effect sizes are standardized and the number of measurement occasions is small. In this study, the authors investigated 4 approaches to correct for this bias. First, the standardized effect sizes are adjusted using Hedges’ small sample bias correction. Next, the within-subject standard deviation is estimated by a 2-level model per study or by using a regression model with the subjects identified using dummy predictor variables. The effect sizes are corrected using an iterative raw data parametric bootstrap procedure. The results indicate that the first and last approach succeed in reducing the bias of the fixed effects estimates. Given the difference in complexity, we recommend the first approach. 相似文献
7.
Tiffany A. Whittaker S. Natasha Beretvas Toni Falbo 《Structural equation modeling》2013,20(2):303-317
The analysis of longitudinal data collected from nonexchangeable dyads presents a challenge for applied researchers for various reasons. This article introduces the dyadic curve-of-factors model (D–COFM), which extends the curve-of-factors model (COFM) proposed by McArdle (1988) for use with nonexchangeable dyadic data. The D–COFM overcomes problems with modeling composite scores across time and instead permits examination of the growth in latent constructs over time. The D–COFM also appropriately models the interdependency among nonexchangeable dyads. Different parameterizations of the D–COFM are illustrated and discussed using a real data set to aid applied researchers when analyzing dyadic longitudinal data. 相似文献
8.
Daniel L. Murphy S. Natasha Beretvas Keenan A. Pituch 《Structural equation modeling》2013,20(3):430-448
This simulation study examined the performance of the curve-of-factors model (COFM) when autocorrelation and growth processes were present in the first-level factor structure. In addition to the standard curve-of factors growth model, 2 new models were examined: one COFM that included a first-order autoregressive autocorrelation parameter, and a second model that included first-order autoregressive and moving average autocorrelation parameters. The results indicated that the estimates of the overall trend in the data were accurate regardless of model specification across most conditions. Variance components estimates were biased across many conditions but improved as sample size and series length increased. In general, the two models that incorporated autocorrelation parameters performed well when sample size and series length were large. The COFM had the best overall performance. 相似文献
9.
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
10.
Daniel H. Robinson Tiffany A. Whittaker Natasha J. Williams S. Natasha Beretvas 《Journal of Experimental Education》2013,81(1):51-64
The authors investigated the influence of effect size and comment inclusion on readers' perceptions of research results. In three experiments, undergraduates, graduates, and faculty read a journal article that either included or did not include an effect size and commentary about the effect size. Contrary to a previous study by Robinson, Fouladi, Williams, and Bera (2002), which concluded that including effect sizes causes readers to overestimate result importance, the authors found that including a comment about the magnitude of the effect size was more important than simply including the effect size in influencing undergraduates' perceptions of research results' importance. Graduate students and faculty members were less influenced by inclusion of either effect sizes or comments. Recommendations concerning effect size and comment inclusion polices are discussed. 相似文献