Growth CurvesThis work describes several statistical techniques for studying repeated measures data, presenting growth curve methods applicable to biomedical, social, animal, agricultural and business research. It details the multivariate development of growth science and repeated measures experiments, covering time-moving covariates, exchangable errors, bioassay results, missing data procedures and nonparametric and Bayesian methods. |
Contents
Preface | 1 |
The Growth Curve Model | 34 |
APPENDIX | 44 |
A Multidimensional Growth Curve Model | 65 |
The Sum of Profiles and Time Moving | 85 |
A Growth Curve Model with Exchangeably | 104 |
Structured Covariance Matrices Model | 116 |
Growth Curves with Incomplete | 143 |
Bayesian Analysis of the PotthoffRoy | 209 |
Common terms and phrases
algorithm analysis Appendix assume assumption Bayesian Chapter columns completely randomized design confidence intervals consider correlation covariance matrix covariance structure data matrix data set denote differences distribution equation error example experimental units F distribution function given groups growth curve coefficients growth curve model illustrate independent intra-class correlation Khatri likelihood ratio Linear Models LTD4 MANOVA maximum likelihood estimates Mean Silicon methods missing data multivariate normal multivariate normal distribution nonparametric null hypothesis observations obtained Phase polynomial Potthoff-Roy model prediction procedure pupil sizes rank regression coefficients rejected repeated measures response sample seemingly unrelated regression SILICON mg/dl simultaneous confidence intervals split-plot Step Study sum of profiles Table techniques test statistics treatment effects univariate V₁ values Var(X variables variance variance-covariance matrix vector Verbyla Wilks Wishart Wishart distribution Y₁ Zeger