Models and analyses for multiple dependent variables

被引:0
|
作者
Herberman, E [1 ]
Figueredo, A [1 ]
机构
[1] Univ Arizona, Tucson, AZ USA
关键词
D O I
暂无
中图分类号
B84 [心理学];
学科分类号
04 ; 0402 ;
摘要
引用
收藏
页码:286 / 286
页数:1
相关论文
共 50 条
  • [41] STRUCTURAL-ANALYSIS OF MODELS WITH COMPOSITE DEPENDENT-VARIABLES
    FARRIS, PW
    PARRY, ME
    AILAWADI, KL
    MARKETING SCIENCE, 1992, 11 (01) : 76 - 94
  • [42] CHOOSING AMONG MULTIPLE NONLINEAR NONNESTED REGRESSION-MODELS WITH DIFFERENT DEPENDENT-VARIABLES - AN APPLICATION TO MONEY DEMAND
    SMITH, MA
    SMYTH, DJ
    ECONOMICS LETTERS, 1990, 34 (02) : 147 - 150
  • [43] Joint analysis of multiple categorical dependent variables in organizational research
    Westfall, Peter
    Hoffman, James J.
    Xia, Jun
    ORGANIZATIONAL RESEARCH METHODS, 2007, 10 (04) : 673 - 688
  • [44] Binary Pattern Recognition in the Presence of Correlated Multiple Dependent Variables
    Deng M.
    Natural Resources Research, 2010, 19 (4) : 269 - 278
  • [45] Functional models for family resemlances modulated by multiple timing variables
    Goldstick, J.
    Shedden, K.
    Zucker, R.
    ALCOHOLISM-CLINICAL AND EXPERIMENTAL RESEARCH, 2008, 32 (06) : 271A - 271A
  • [46] Relationship of the Reproducibility of Multiple Variables among Global Climate Models
    Nishii, Kazuaki
    Miyasaka, Takafumi
    Nakamura, Hisashi
    Kosaka, Yu
    Yokoi, Satoru
    Takayabu, Yukari N.
    Endo, Hirokazu
    Ichikawa, Hiroki
    Inoue, Tomoshige
    Oshima, Kazuhiro
    Sato, Naoki
    Tsushima, Yoko
    JOURNAL OF THE METEOROLOGICAL SOCIETY OF JAPAN, 2012, 90A : 87 - 100
  • [47] Optimal designs for binary response models with multiple nonnegative variables
    Huang, Shih-Hao
    Lo Huang, Mong-Na
    Lin, Cheng-Wei
    JOURNAL OF STATISTICAL PLANNING AND INFERENCE, 2020, 206 : 75 - 83
  • [48] Multiple Imputation of Predictor Variables Using Generalized Additive Models
    De Jong, Roel
    Van Buuren, Stef
    Spiess, Martin
    COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, 2016, 45 (03) : 968 - 985
  • [49] Multiple Response Variables Regression Models in R: The mcglm Package
    Bonat, Wagner Hugo
    JOURNAL OF STATISTICAL SOFTWARE, 2018, 84 (04): : 1 - 30
  • [50] Selection of Latent Variables for Multiple Mixed-outcome Models
    Zhou, Ling
    Lin, Huazhen
    Song, Xinyuan
    Li, Yi
    SCANDINAVIAN JOURNAL OF STATISTICS, 2014, 41 (04) : 1064 - 1082