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Measuring Intra-individual Change at Two or More Occasions with Hypothesis Testing Methods

機(jī)譯：用假設(shè)檢驗(yàn)方法測量兩種或兩種以上情況下的個(gè)體內(nèi)部變化

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摘要

The present study proposed six new omnibus hypothesis tests---F1, F2, LR, ST and two chi-squared based statistics---to measure psychometric significance of individual change when an individual is measured at two or more occasions. The hypothesis tests were evaluated on criteria of Type I error, power, and agreement between the methods in the adaptive measurement of change (AMC) framework. This study expanded on AMC research by Finkleman, Weiss and Kim-Kang (2010) and Lee (2015), by introducing more generalized methods for multi-occasion case. The omnibus tests were evaluated under various discrimination, bank type, and change conditions. The simulation results showed the LR test to achieve an optimum balance between Type I error and power. The hypothesis tests were found to be robust under most testing conditions. The tests were successfully applied to K-12 math data. The proposed methods are applicable under a variety of testing conditions in which IRT-based item parameters have been established.
機(jī)譯：本研究提出了六種新的綜合假設(shè)檢驗(yàn)-F1，F(xiàn)2，LR，ST和兩個(gè)基于卡方的統(tǒng)計(jì)數(shù)據(jù)-用以測量在兩次或更多次測量個(gè)體時(shí)個(gè)體變化的心理測量意義。假設(shè)檢驗(yàn)是根據(jù)I類錯(cuò)誤，功效以及適應(yīng)性變化度量（AMC）框架中方法之間的一致性的標(biāo)準(zhǔn)進(jìn)行評估的。這項(xiàng)研究通過引入針對多種情況的更通用方法，擴(kuò)展了Finkleman，Weiss和Kim-Kang（2010）和Lee（2015）進(jìn)行的AMC研究。綜合測試是在各種區(qū)分度，銀行類型和變更條件下進(jìn)行評估的。仿真結(jié)果表明，LR測試在I型誤差和功率之間實(shí)現(xiàn)了最佳平衡。假設(shè)測試在大多數(shù)測試條件下都非?？煽俊y試已成功應(yīng)用于K-12數(shù)學(xué)數(shù)據(jù)。所提出的方法適用于已建立基于IRT的項(xiàng)目參數(shù)的各種測試條件。

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  • 作者

    Phadke, Chaitali.;

  • 作者單位

    University of Minnesota.;

  • 授予單位 University of Minnesota.;
  • 學(xué)科 Quantitative psychology.;Psychobiology.
  • 學(xué)位 Ph.D.
  • 年度 2017
  • 頁碼 205 p.
  • 總頁數(shù) 205
  • 原文格式 PDF
  • 正文語種 eng
  • 中圖分類
  • 關(guān)鍵詞

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