Michigan State University Home
  • MSU Libraries
  • Digital Repository
  • Home
  • About
  • Collections
Selected filters
  • Subject: Educational statistics
    ×
  • Electronic Theses & Dissertations
    5
  • Theses
    5
  • English
    5
  • In Copyright
    5
  • Approximation theory
    1
  • Education--Research--Methodology
    1
  • Educational evaluation--Statistical methods
    1
  • Estimation theory
    1
  • Factor analysis
    1
  • Linear models (Statistics)
    1
  • Marginal distributions
    1
  • Mathematical statistics
    1
  • Monte Carlo method
    1
  • Multilevel models (Statistics)
    1
  • Regression analysis
    1
  • Sampling (Statistics)
    1
  • United States
    1
  • Universities and colleges
    1
Year
TO

Search results for Policy Review

Showing 1 to 5 of 5 results
  • Large and small sample properties of maximum likelihood estimates for the hierarchical linear model

    Bassiri, Dina
    Text (1988)
    Part of Electronic Theses & Dissertations
    In Copyright
  • A mixed linear model with two-way crossed random effects and estimation via the EM algorithm

    Kang, Sang-jin
    Text (1992)
    Part of Electronic Theses & Dissertations
    In Copyright
  • A comparison of alternative approximations to maximum likelihood estimation for hierarchical generalized linear models : the logistic-normal model case

    Yosef, Matheos
    Text (2001)
    Part of Electronic Theses & Dissertations
    In Copyright
  • Statistics and social science : the introduction of inferential statistics into higher education in America from 1890 to 1930

    Dobbertin, Gerald Frederick
    Text (1981)
    Part of Electronic Theses & Dissertations
    In Copyright
  • Incorporating factor analysis into hierarchical models

    Miyazaki, Yasuo
    Text (2000)
    Part of Electronic Theses & Dissertations
    In Copyright
  • First
  • 1(current)
  • Last
  • Call MSU: (517) 355-1855
  • Visit: msu.edu
  • Notice of Nondiscrimination
  • SPARTANS WILL.
  • © Michigan State University
Michigan State University Wordmark