Modelling hearing thresholds in the elderly.

This paper concerns a linear mixed-effects repeated measures model in the analysis of a large data set with over 17,000 observations in a longitudinal study of pure-tone hearing perception in the elderly. The repeated measurements are described by fixed and random components in the model. The fixed effects include the age at entry, time of follow-up, a quadratic component in natural logarithm of frequency, a component to allow for participants with hearing impairments, as well as interaction terms between age and frequency and between impairment and frequency. The random factors include a term for subject, a time component and a frequency component. The analysis shows that hearing impaired individuals have similar patterns of hearing loss over time but, on average, have higher hearing thresholds than normal individuals. Estimation of the random effects in the model by restricted maximum likelihood (REML) using the Newton-Raphson method made possible the analysis of this large data set with speed and efficiency.

[1]  F. Bess,et al.  Hearing Impairment as a Determinant of Function in the Elderly , 1989, Journal of the American Geriatrics Society.

[2]  John F. Corso,et al.  Age and Sex Differences in Pure‐Tone Thresholds , 1959 .

[3]  D. W. Robinson,et al.  Age effect in hearing - a comparative analysis of published threshold data. , 1979, Audiology : official organ of the International Society of Audiology.

[4]  Christine Waternaux,et al.  Methods for Analysis of Longitudinal Data: Blood-Lead Concentrations and Cognitive Development , 1989 .

[5]  J. Fozard,et al.  Age changes in pure-tone hearing thresholds in a longitudinal study of normal human aging. , 1990, The Journal of the Acoustical Society of America.

[6]  J. Liukkonen,et al.  A comparative study of three methods for analysing longitudinal pulmonary function data. , 1988, Statistics in medicine.

[7]  D. Harville Bayesian inference for variance components using only error contrasts , 1974 .

[8]  N. Laird,et al.  Maximum likelihood computations with repeated measures: application of the EM algorithm , 1987 .

[9]  David Arenberg,et al.  Normal Human Aging: The Baltimore Longitudinal Study on Aging , 1984 .

[10]  Calyampudi R. Rao,et al.  The theory of least squares when the parameters are stochastic and its application to the analysis of growth curves. , 1965, Biometrika.

[11]  J. Peixoto Hierarchical Variable Selection in Polynomial Regression Models , 1987 .

[12]  J. F. Corso Age and sex differences in pure-tone thresholds. Survey of hearing levels from 18 to 65 years. , 1963, Archives of otolaryngology.

[13]  J. Peixoto A Property of Well-Formulated Polynomial Regression Models , 1990 .

[14]  H. Weisberg,et al.  Empirical Bayes estimation of individual growth-curve parameters and their relationship to covariates. , 1983, Biometrics.

[15]  E. Mościcki,et al.  Hearing Loss in the Elderly: An Epidemiologic Study of the Framingham Heart Study Cohort , 1985, Ear and hearing.

[16]  Douglas M. Bates,et al.  A Relative Off set Orthogonality Convergence Criterion for Nonlinear least Squares , 1981 .

[17]  R HINCHCLIFFE,et al.  The pattern of the threshold of perception for hearing and other special senses as a function of age. , 1958, Gerontologia.

[18]  J. Ware Linear Models for the Analysis of Longitudinal Studies , 1985 .

[19]  M. Møller Hearing in 70 and 75 year old people: results from a cross sectional and longitudinal population study. , 1981, American journal of otolaryngology.

[20]  J. Ware,et al.  Random-effects models for longitudinal data. , 1982, Biometrics.

[21]  P. Vacek,et al.  Application of a two-stage random effects model to longitudinal pulmonary function data from sarcoidosis patients. , 1989, Statistics in medicine.

[22]  D. Bates,et al.  Newton-Raphson and EM Algorithms for Linear Mixed-Effects Models for Repeated-Measures Data , 1988 .

[23]  D. Harville Maximum Likelihood Approaches to Variance Component Estimation and to Related Problems , 1977 .

[24]  K Y Liang,et al.  Longitudinal data analysis for discrete and continuous outcomes. , 1986, Biometrics.