Stability of INFIT and OUTFIT Compared to Simulated Estimates in Applied Setting.

Journal of applied measurement Pub Date : 2017-01-01
Kari J Hodge, Grant B Morgan
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Abstract

Residual-based fit statistics are commonly used as an indication of the extent to which the item response data fit the Rash model. Fit statistic estimates are influenced by sample size and rules-of thumb estimates may result in incorrect conclusions about the extent to which the model fits the data. Estimates obtained in this analysis were compared to 250 simulated data sets to examine the stability of the estimates. All INFIT estimates were within the rule-of-thumb range of 0.7 to 1.3. However, only 82% of the INFIT estimates fell within the 2.5th and 97.5th percentile of the simulated item's INFIT distributions using this 95% confidence-like interval. This is a 18 percentage point difference in items that were classified as acceptable. Fourty-eight percent of OUTFIT estimates fell within the 0.7 to 1.3 rule- of-thumb range. Whereas 34% of OUTFIT estimates fell within the 2.5th and 97.5th percentile of the simulated item's OUTFIT distributions. This is a 13 percentage point difference in items that were classified as acceptable. When using the rule-of- thumb ranges for fit estimates the magnitude of misfit was smaller than with the 95% confidence interval of the simulated distribution. The findings indicate that the use of confidence intervals as critical values for fit statistics leads to different model data fit conclusions than traditional rule of thumb critical values.

应用环境下INFIT和OUTFIT的稳定性与模拟估计的比较。
基于残差的拟合统计通常被用作项目反应数据与拉什模型拟合程度的指示。拟合统计估计受样本量的影响,经验法则估计可能导致关于模型拟合数据程度的错误结论。将分析中获得的估计值与250个模拟数据集进行比较,以检查估计值的稳定性。所有INFIT估计都在0.7到1.3的经验范围内。然而,使用95%置信区间,只有82%的INFIT估计值落在模拟项目的INFIT分布的2.5和97.5%之间。在可接受的项目中,这是18个百分点的差异。OUTFIT估计的48%落在0.7到1.3的经验范围内。而34%的OUTFIT估计落在模拟项目的OUTFIT分布的2.5和97.5%之间。在可接受的项目中,这是13个百分点的差异。当使用经验法则范围进行拟合估计时,失配的幅度小于模拟分布的95%置信区间。研究结果表明,与传统的经验法则临界值相比,使用置信区间作为拟合统计的临界值导致模型数据拟合结论不同。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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