When combining results from separate investigations in a meta-analysis, random effects methods enable the modelling of differences between studies by incorporating a heterogeneity parameter that accounts explicitly for across-study variation. We develop a simple form for the variance of Cochran's ho
Estimation of Fixed and Random Effects in the Functional Nonlinear Errors-in-Variable Model
β Scribed by Dr. P. M. Johnson; Dr. G. A. Milliken
- Publisher
- John Wiley and Sons
- Year
- 1985
- Tongue
- English
- Weight
- 398 KB
- Volume
- 27
- Category
- Article
- ISSN
- 0323-3847
No coin nor oath required. For personal study only.
β¦ Synopsis
Abatrcrct
Consider an experiment where a nonlinear continuous functional relationship exists between y and 5. Assume that this relationship haa been meaaured at n replicatad pointa of X from each of t treatmenta or populations. Assume further that the X are fixed unknown vectors and that the location parameter S is either B fixed unknown vector or a vector of random variables. In the firat case various linear hypotheees are to be tested about S, such as teats for main effects and interaction; in the second case, the mean and variance of the random variable 2 are to be estimated. A twostep procedure based on asymptotic theory is presented to test hypothesee or develop estimates for the fixed effecta or random effecta functional errors-in-variable model. An example of a one-way random effecta model is given.
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