Latent Variable and Latent Structure Models (Quantitative Methodology Series)

個数：

Latent Variable and Latent Structure Models (Quantitative Methodology Series)

  • 提携先の海外書籍取次会社に在庫がございます。通常3週間で発送いたします。
    【重要ご説明事項】
    1. 納期遅延や、ご入手不能となる場合が若干ございます。
    2. 複数冊ご注文の場合、分割発送となる場合がございます。
    3. 美品のご指定は承りかねます。
  • 【入荷遅延について】
    世界情勢の影響により、海外からお取り寄せとなる洋書・洋古書の入荷が、表示している標準的な納期よりも遅延する場合がございます。
    おそれいりますが、あらかじめご了承くださいますようお願い申し上げます。
  • ◆画像の表紙や帯等は実物とは異なる場合があります。
  • ◆ウェブストアでの洋書販売価格は、弊社店舗等での販売価格とは異なります。
    また、洋書販売価格は、ご注文確定時点での日本円価格となります。
    ご注文確定後に、同じ洋書の販売価格が変動しても、それは反映されません。
  • 製本 Hardcover:ハードカバー版／ページ数 292 p.
  • 言語 ENG
  • 商品コード 9780805840469
  • DDC分類 511.8

基本説明

Based on material presented at the 22nd biennial conference of the Society for Multivariate Analysis in the Behavioral Sciences (SMABS).

Full Description

This edited volume features cutting-edge topics from the leading researchers in the areas of latent variable modeling. Content highlights include coverage of approaches dealing with missing values, semi-parametric estimation, robust analysis, hierarchical data, factor scores, multi-group analysis, and model testing. New methodological topics are illustrated with real applications. The material presented brings together two traditions: psychometrics and structural equation modeling. Latent Variable and Latent Structure Models' thought-provoking chapters from the leading researchers in the area will help to stimulate ideas for further research for many years to come.

This volume will be of interest to researchers and practitioners from a wide variety of disciplines, including biology, business, economics, education, medicine, psychology, sociology, and other social and behavioral sciences. A working knowledge of basic multivariate statistics and measurement theory is assumed.

Contents

Contents: Preface. D.J. Bartholomew, Old and New Approaches to Latent Variable Modelling. I. Moustaki, C. O'Muircheartaigh, Locating "Don't Know," "No Answer" and Middle Alternatives on an Attitude Scale: A Latent Variable Approach. L.A. van der Ark, B.T. Hemker, K. Sijtsma, Hierarchically Related Nonparametric IRT Models, and Practical Data Analysis Methods. P. Tzamourani, M. Knott, Fully Semiparametric Estimation of the Two-Parameter Latent Trait Model for Binary Data. P. Rivera, A. Satorra, Analyzing Group Differences: A Comparison of SEM Approaches. R.D. Wiggins, A. Sacker, Strategies for Handling Missing Data in SEM: A User's Perspective. T. Raykov, S. Penev, Exploring Structural Equation Model Misspecifications Via Latent Individual Residuals. J-Q. Shi, S-Y. Lee, B-C. Wei, On Confidence Regions of SEM Models. P. Filzmoser, Robust Factor Analysis: Methods and Applications. M. Croon, Using Predicted Latent Scores in General Latent Structure Models. H. Goldstein, W. Browne, Multilevel Factor Analysis Modelling Using Markov Chain Monte Carlo Estimation. J-P. Fox, C.A.W. Glas, Modelling Measurement Error in Structural Multilevel Models.