Obtaining Reliable Likelihood Ratio Tests from Simulated Likelihood Functions

Obtaining Reliable Likelihood Ratio Tests from Simulated Likelihood Functions

MIXED MODELS Models allowing for continuous heterogeneity by assuming that value of one or more parameters follow a specified distribution have become increasingly popular. This is known as 'mixing' parameters, and it is standard practice by researchers--and the default option in many statistical programs--to base test statistics for mixed models on simulations using asymmetric draws (e.g. Halt...

Likelihood Ratio Tests for Monotone Functions

Ve study the problem of testing for equality at a fixed point in the setting of nonparametric estimation of a monotone function. The likelihood ratio test for this hypothesis is derived in the particular case of interval censoring (or current status data) and its limiting distribution is obtained. The limiting distribution is that of the integral of the difference of the squared slope processes...

Maximum Likelihood Estimation and Likelihood-ratio Tests

The method of maximum likelihood (ML), introduced by Fisher (1921), is widely used in human and quantitative genetics and we draw upon this approach throughout the book, especially in Chapters 13–16 (mixture distributions) and 26–27 (variance component estimation). Weir (1996) gives a useful introduction with genetic applications, while Kendall and Stuart (1979) and Edwards (1992) provide more ...

Likelihood Ratio Tests

Previously, we have employed a program (Jtest) to test an hypothesis involving many parameters (multiple constraints). This test, which involves comparing parameter estimates with hypothesized values, is known as a Wald test. We also used the Jtest program to compare two di¤erent estimators in a Hausman test. There is an alternative method for conducting joint tests, which can be implemented ea...

likelihood ratio tests