Biomedical subjects

N M Laird

Publications and source records attributed to N M Laird.

78 records · Page 5Linked to original sources

PubMedDate not supplied

Model-based approaches to analysing incomplete longitudinal and failure time data.

Since Wu and Carroll (Biometrics 44, 175-188) proposed a model for longitudinal progression in the presence of informative dropout, several researchers have developed and studied models for situations where both a vector of repeated outcomes and an event time is available for each subject. These models have been developed for either longitudinal studies with dropout or for survival studies in which a random, time-varying covariate is measured repeatedly across time. When inference about the longitudinal variable is of interest, event times are treated as covariates and are often incomplete due to censoring. If survival or event time is the primary endpoint, repeated outcomes observed prior to the event are viewed as covariates; this covariate process is often incomplete, measured with error, or observed at unscheduled times during the study. We review several models which are used to handle incomplete response and covariate data in both survival and longitudinal studies.

Algorithms↗

PubMedDate not supplied

Missing data in longitudinal studies.

When observations are made repeatedly over time on the same experimental units, unbalanced patterns of observations are a common occurrence. This complication makes standard analyses more difficult or inappropriate to implement, means loss of efficiency, and may introduce bias into the results as well. Some possible approaches to dealing with missing data include complete case analyses, univariate analyses with adjustments for variance estimates, two-step analyses, and likelihood based approaches. Likelihood approaches can be further categorized as to whether or not an explicit model is introduced for the non-response mechanism. This paper will review the use of likelihood based analyses for longitudinal data with missing responses, both from the point of view of ease of implementation and appropriateness in view of the non-response mechanism. Models for both measured and dichotomous outcome data will be discussed. The appropriateness of some non-likelihood based analyses is briefly considered.

Algorithms↗

PubMedDate not supplied

An analysis of two-period crossover designs with carry-over effects.

The crossover design is a type of longitudinal study with subjects receiving different treatments in different time periods. When carry-over effects are absent, the usual crossover design is structured so that all the information about treatment effects is contained in the within-subject contrasts; standard analyses are based on these within-subject contrasts and ignore any between-subject information. With carry-over effects present these standard analyses can be very inefficient, especially for suboptimal designs. We describe alternative approaches based on methods for the analysis of longitudinal data.

Longitudinal Studies↗

PubMedDate not supplied

Nonlinear growth curve analysis: estimating the population parameters.

A model for analysing longitudinal growth data with covariates is proposed. It assumes that the data for each individual follow a nonlinear growth model, with parameters unique to that individual. The parameters of individuals are assumed to vary in the population, with the population mean of each parameter dependent upon covariates. Several simple, two-stage methods of estimation are described and compared for making inferences about the effects of covariates upon growth. We also present a method of model validation for nonlinear models. These two-stage methods solve the inference problem we encounter when performing multiple cross-sectional analyses of the effects of covariates along the age scale. In addition, these two-stage methods permit us to study the effects of covariates upon growth rate, or other, possibly nonlinear, growth parameters. We find that some methods are better than others at reproducing the covariate effects observed in a series of age-specific analyses of the data.

Age Factors↗

PubMedDate not supplied

Longitudinal analysis of incomplete adolescent data.

An approach is illustrated for the analysis of longitudinal variables collected during adolescence. Since the method requires complete data, three techniques are compared for application when some individuals have missing values. These methods are implemented in a study of systolic blood pressures and dietary fat intakes collected longitudinally in adolescent girls. The value of adolescent systolic and fat variables in predicting systolic pressure in adult women is investigated.

Adolescent↗

PubMedDate not supplied

[Validity and reproducibility of a questionnaire on physical activity and non-activity for school children in Mexico City].

OBJECTIVE: To assess the validity and reproducibility of a self-reported questionnaire on physical activity and inactivity, developed for children aged 10-14 in Mexico City. MATERIAL AND METHODS: Between May and December 1996, a self-reported physical activity and inactivity questionnaire was developed and applied twice to a sample of 114 students aged 10 to 14, from a low and middle income population of Mexico City. The children's mothers completed the same questionnaire, and two 24-hour recalls of physical activity were used for comparison. Statistical analysis consisted of central tendency and dispersion measures and Pearson's correlation coefficient. RESULTS: Correlations between hours per day spent in physical activity and inactivity from the children's questionnaire and the 24-hour recall data, were 0.03 for moderate activity, 0.15 for vigorous activity, and 0.51 (p = 0.001) for watching television, adjusted by age, gender, town, and illness prior to the administration of the questionnaire. Compared to the 24-hour recall data, the questionnaire overestimated the time spent watching television, reading or participating in vigorous activity, and underestimated the time engaged in moderate activity. Statistically significant (p < 0.05) six-month reproducibility values were observed for watching television (r = 0.53), sleeping (r = 0.40), moderate (r = 0.38), and vigorous activity (r = 0.55). CONCLUSIONS: Among children of Mexico City aged 10-14, the questionnaire showed acceptable validity in estimating the time watching television, and acceptable reproducibility of the time watching television, vigorous and moderate activity.

Adolescent↗