本書的目的在于為教育實踐者在考試數據分析中應該使用哪種方法以及如何使用該方法提出具體化和合理化的建議。研究結果有助于提高多組被試測量結果比較的可靠性和有效性，避免在應用傳統方法時對參數指數的錯誤選擇所帶來的影響，發揮Benjamini Hochberg法和校準法在這方面的潛在優勢。
張明才，博士，現為齊魯師范學院教師教育學院副教授。2020年獲美國密歇根州立大學哲學博士學位，專業為測量與數量方法。曾參與美國國家科學基金會和美國教育部等機構的研究項目，并在密歇根州立大學統計培訓與咨詢中心擔任統計分析咨詢員。研究方向為項目反應理論和結構方程模型在教育測量中的應用。在Structural Equation Modeling-A Multi-disciplinary Journal、 Reading andWriting、Genetica等SSCI/SCI 學術期刊發表論文多篇。
List of Tables
List of Figures
Chapter 1 An Overview
1.1 Introduction
1.2 Statement of the Problem
1.3 Purpose and Significance of the Study
1.4 Organization of the Book
Chapter 2 Theoretical Background of Measurement N0ninvariance
2.1 Introduction
2.2 The Concept of MI in LVM
2.3 Levels of MI
2.4 Violations of MI
2.5 Methods of Detecting Measurement Noninvariance
2.6 Chapter Summary
Chapter 3 Detection of Measurement Noninvarianee in a Simulated Study
3.1 Introduction
3.2 Simulation Design
3.3 Data Generation
3.4 Data Analysis Procedure
3.5 Evaluation Criteria
3.6 Results of the Simulation Study
3.7 Chapter Summary
Chapter 4 Detection of Measurement Noninvariance in an Empirical Study
4.1 Introduction
4.2 Empirical Dataset
4.3 Data Analysis Procedure
4.4 The Choice of an RI for the FR Method
4.5 Results of the Empirical Study
4.6 Chapter Summary
Chapter 5 Conclusions and Recommendations
5.1 Introduction
5.2 Summary of Findings
5.3 Comments on the Performances of the Three Methods
5.4 Implications and Recommendations
5.5 Limitations
Appendix A Technical Details for the B-H Method
Appendix B Technical Details for the AM Method
References
Postscript
新書資訊