<abstract xmlns="http://www.w3.org/1999/xhtml"><p> There are several linear and nonlinear models for analyzing repeated measurements. The mean response for an individual depends on the regression parameters specific to that individual. One of the simple forms is the sum of vectors of fixed parameters and random effects. When the models with mixed effects for several groups are parallel, pairwise comparisons of level differences are considered. For the comparisons, approximate simultaneous confidence intervals are given.</p></abstract>

There are several linear and nonlinear models for analyzing repeated measurements. The mean response for an individual depends on the regression parameters specific to that individual. One of the simple forms is the sum of vectors of fixed parameters and random effects. When the models with mixed effects for several groups are parallel, pairwise comparisons of level differences are considered. For the comparisons, approximate simultaneous confidence intervals are given.

Pairwise comparisons for parallel profile models with mixed effects

Faculty of Mathematics Kyushu University Motooka, Nishi-ku, Fukuoka 819-0395 JAPAN

Tatra Mountains Mathematical Publications

{"article-title":"Pairwise comparisons for parallel profile models with mixed effects"}

There are several linear and nonlinear models for analyzing repeated measurements. The mean response for an individual depends on the regression parameters...

Pairwise comparisons for parallel profile models with mixed effects

Online veröffentlicht: 13. Nov. 2012

Seitenbereich: 67 - 73

DOI: https://doi.org/10.2478/v10127-012-0007-y

Schlüsselwörter
confidence interval, nonlinear model, repeated measurements.

This content is open access.

Pairwise comparisons for parallel profile models with mixed effects

Online veröffentlicht: 13. Nov. 2012

Seitenbereich: 67 - 73

DOI: https://doi.org/10.2478/v10127-012-0007-y

Schlüsselwörterconfidence interval, nonlinear model, repeated measurements.

This content is open access.

Schlüsselwörter
confidence interval, nonlinear model, repeated measurements.