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PubMed1991

Longitudinal Gompertzian analysis of lung cancer mortality in the U.S., 1968-1986. Rising lung cancer mortality is the natural consequence of competitive deterministic mortality dynamics.

Age-adjusted mortality rates for lung cancer (LC) in the United States from 1968 to 1986 were subjected to longitudinal Gompertzian analysis. Age-adjusted LC mortality rate distributions between age 20 and 50 years were determined by a variable environmental factor and a common intersect point. The environmental factor declined (improved) 1.89-fold for men and 3.11-fold for women in 1986 as compared to 1968. The age at the common intersect point was 47.2 years for men and 39.1 years for women. Between 1968 and 1986, the non-age-standardized annual crude LC mortality rate increased 44.8% for men and 217.6% for women. Longitudinal Gompertzian analysis of LC mortality data suggests that the rising LC mortality rates in the United States are the natural consequence of competitive deterministic mortality dynamics and not a reflection of an environment that is directly more conductive to LC mortality. That is, more people are dying of LC because they are not dying from other diseases such as ischemic heart disease and stroke. Longitudinal Gompertzian analysis demonstrates that single disease mortality should not be studied in isolation, but rather examined in relation to other causes of death. When viewed from this perspective, the basis for the more dramatic rise in LC mortality in women becomes immediately evident.

Adult↗

PubMed2002

[Active life expectancy in Germany and in the United States. A cohort analysis based on the "German Socio-Economic Panel" (GSOEP) and the "Panel Study of Income Dynamics" (PSID)].

Using the method of multistate life-tables, the article presents results on active life expectancy on the basis of the German Socio-Economic Panel (GSOEP) and the Panel Study of Income Dynamics (PSID). The transitions into and out of active life are based on event-history analysis and are calculated for different cohorts. Compared to cross-sectional analysis, the longitudinal analysis carried out here describes active life expectancy with reference to single birth cohorts. Results show that in Germany there has been substantial improvement in active life expectancy while in the USA there has been some deterioration.

Activities of Daily Living↗

PubMed2005

Circulating Valpha24+Vbeta11+ NKT cell numbers and dendritic cell CD1d expression in hepatitis C virus infected patients.

CD1d-restricted natural killer T (NKT) cells are involved in the regulation of various immune responses, and have been shown to inhibit viral replication in animal hepatitis models when activated by the glycolipid alpha-galactosylceramide (alpha-GalCer, KRN7000). Previous studies have indicated that alpha-GalCer-induced activation of the immune system requires both CD1d expression by antigen-presenting cells as well as (normal) numbers of NKT cells. Discrepancies exist over circulating numbers of human invariant Valpha24+Vbeta11+ NKT cells during hepatitis C virus (HCV) infection. Here, by cross-sectional analysis and longitudinal analysis of patients undergoing effective combination antiviral therapy, we demonstrate that circulating Valpha24+Vbeta11+ NKT cell numbers are not decreased during active HCV infection. Importantly, as we also show that CD1d is expressed at comparable levels by peripheral blood monocytes and CD1c+ myeloid dendritic cells (DC) of healthy individuals and HCV-infected patients, these data indicate that all ingredients for evaluating the antiviral effects of the Valpha24+Vbeta11+ NKT cell ligand alpha-GalCer in HCV-infected patients are present.

Adult↗

PubMed2003

Genetic linkage analysis of longitudinal hypertension phenotypes using three summary measures.

BACKGROUND: Longitudinal data often have multiple (repeated) measures recorded along a time trajectory. For example, the two cohorts from the Framingham Heart Study (GAW13 Problem 1) contain 21 and 5 repeated measures for hypertension phenotypes as well as epidemiological risk factors, respectively. Direct modelling of a large number of serially and biologically correlated traits in the context of linkage analysis can be prohibitively complex. Alternatively, we may consider using univariate transformation for linkage analysis of longitudinal repeated measures. RESULTS: We evaluated the utility of three conventional summary measures (mean, slope, and principal components) for genetic linkage analysis of longitudinal phenotypes by analyzing the chromosome 10 data of the Framingham Heart Study. Except for the temporal slope, all of the summary methods and the multivariate analysis identified the previously reported region, marker GATA64A09, for systolic blood pressure or high blood pressure. Further analysis revealed that this region may harbor gene(s) affecting human blood pressure at multiple stages of life. CONCLUSION: We conclude that mean and principal components are feasible alternatives for genetic linkage analysis of longitudinal phenotypes, but the slope might have a separate genetic basis from that of the original longitudinal phenotypes.

Adult Children↗

PubMed2004

Measurement of inferior vena cava diameter for evaluation of venous return in subjects on day 10 of a bed-rest experiment.

We evaluated the usefulness of measurements of the inferior vena cava (IVC) diameters on abdominal echograms as an indicator of changes of venous return in subjects with orthostatic intolerance (OI) induced by simulated microgravity. We performed a standing test and recorded the IVC diameters on abdominal echograms in 12 subjects placed on a 20-day 6 degrees head-down-tilt bed-rest experiment. We found that different patterns of changes in IVC diameter occurred in the standing test on day 10 of the experiment; in five subjects with a marginal decrease in pulse pressure, IVC diameters in the upright position were markedly decreased compared with those in the supine position. In five subjects with feelings of discomfort, the IVC diameters in the upright position distended or did not decrease from those in the supine position. These results suggested that the changes in IVC diameter on the standing test indicated the presence of various types of hemodynamic responses of OI caused by simulated microgravity. In this study, we also evaluated changes in body-water compartments by conducting multifrequency bioelectrical impedance analysis. Longitudinal data analysis showed that the total body-water-to-fat-free mass and extracellular fluid-to-fat-free mass ratios decreased during the experimental period and recovered thereafter, and that the ratio of intracellular fluid to fat-free mass decreased during the experiment. No significant difference in changes in body-water compartments was seen among subjects with different patterns of changes in IVC diameters. Measurement of IVC diameter was useful to estimate hemodynamic changes in subjects with OI.

Adult↗

PubMed2005

Regression models for the analysis of longitudinal Gaussian data from multiple sources.

We present a regression model for the joint analysis of longitudinal multiple source Gaussian data. Longitudinal multiple source data arise when repeated measurements are taken from two or more sources, and each source provides a measure of the same underlying variable and on the same scale. This type of data generally produces a relatively large number of observations per subject; thus estimation of an unstructured covariance matrix often may not be possible. We consider two methods by which parsimonious models for the covariance can be obtained for longitudinal multiple source data. The methods are illustrated with an example of multiple informant data arising from a longitudinal interventional trial in psychiatry.

Adolescent↗

PubMed1991

Longitudinal Gompertzian analysis of primary malignant brain tumor mortality in the U.S., 1962-1987: rising mortality in the elderly is the natural consequence of competitive deterministic dynamics.

Age-adjusted mortality rates for primary malignant brain tumors (PMBT) in the United States from 1962 to 1987 were subjected to longitudinal Gompertzian analysis. Age-adjusted PMBT mortality rate distributions between age 25 and 65 years were determined by a variable environmental factor and a common intersect point. The environmental factor declined (improved) 1.58-fold for men and 2.34-fold for women in 1987 as compared to 1962. The age at the common intersect point was 68.4 years for men and 64.1 years for women. Between 1962 and 1987, non-age-standardized annual crude PMBT mortality rates increased 14.5% for men and 37.8% for women. However, PMBT mortality rates at age 77.5 years rose 259% for men and 409% for women between 1962 and 1987. Longitudinal Gompertzian analysis of PMBT mortality data suggests that rapidly rising PMBT mortality rates in the elderly are the natural consequence of competitive deterministic mortality dynamics and should not be attributed to environmental factors, past or present, that are directly contributing to PMBT mortality. Furthermore, longitudinal Gompertzian analysis demonstrates that PMBT mortality should not be studied in isolation, but rather should be examined in relation to other causes of death. When viewed from this perspective, the basis for the dramatic rise in PMBT mortality in the elderly becomes quite evident.

Adult↗

PubMed2000

Modern statistical techniques for the analysis of longitudinal data in biomedical research.

Longitudinal study designs in biomedical research are motivated by the need or desire of a researcher to assess the change over time of an outcome and what risk factors may be associated with the outcome. The outcome is measured repeatedly over time for every individual in the study, and risk factors may be measured repeatedly over time or they may be static. For example, many clinical studies involving chronic obstructive pulmonary disease (COPD) use pulmonary function as a primary outcome and measure it repeatedly over time for each individual. There are many issues, both practical and theoretical, which make the analysis of longitudinal data complicated. Fortunately, advances in statistical theory and computer technology over the past two decades have made techniques for the analysis of longitudinal data more readily available for data analysts. The aim of this paper is to provide a discussion of the important features of longitudinal data and review two popular modern statistical techniques used in biomedical research for the analysis of longitudinal data: the general linear mixed model, and generalized estimating equations. Examples are provided, using the study of pulmonary function in cystic fibrosis research.

Biometry↗

PubMed1979

Analysis of longitudinal twin data. Basic model and applications to physical growth measures.

A formal model is presented for the analysis of longitudinal twin data, based on the underlying analysis-of-variance model for repeated measures. The model is developed in terms of the expected values for the variance components representing twin concordance, and the derivation is provided for computing within-pair (intraclass) correlations, and for estimating the percent of variance explained by each component. The procedures are illustrated with physical growth data extending from birth to six years, and concordance estimates are obtained for average size and for the pattern of spurts and lags in growth. A test of significance is also described for comparing monozygotic twins with dizygotic twins. The procedures are particularly useful for assessing chronogenetic influences on development, especially whether the episodes of acceleration and lag occur in parallel for genetically matched twins. The model may be employed with psychological data also.

Analysis of Variance↗

PubMed1995

Longitudinal Gompertzian analysis of Parkinson's disease mortality in Japan, 1950-1993.

Age-specific mortality rates from Parkinson's disease (PD) in Japan from 1950 through 1993 were subjected to longitudinal Gompertzian analysis. Age-specific PD mortality rate distributions between age 45 and 75 years were determined by a common fixed intersection point and a variable competitive factor. The intersection point for PD occurred at age 65.36 years and mortality rate 2.45 per 100,000 for men, and at age 65.49 years and mortality rate 2.12 per 100,000 for women from 1950-1951 to 1992-1993. The increase in PD mortality is due entirely to rapidly increasing age-specific mortality rates at ages greater than the intersection points for both sexes. Longitudinal Gompertzian analysis suggests that the rising mortality from PD has been the consequence of competitive influences upon PD mortality dynamics.

Age Factors↗

PubMed2002

On the joint analysis of longitudinal responses and early discontinuation in randomized trials.

Our focus is on the joint analysis of longitudinal nonnormal responses and early discontinuation in (pre)-clinical trials. Separate models are fitted to the two series (response and discontinuation) to account for covariate and time effects. The serial dependence and the dependence between response and drop-out are also modeled. This is done using particular dependence functions, called copulas. Copulas are used to create a joint distribution with given marginal distributions. Applications are given for the analysis of heart rate/morbidity in toxicology and pain severity/intake of rescue medications in a trial on migraine. Using copulas, the level of dependence between two variables remains invariant to changes in the marginal distribution of either variable. This proves interesting in modeling the association in a longitudinal setting when responses change over time.

Algorithms↗

PubMed2003

Linkage analysis of longitudinal data.

BACKGROUND: We propose a statistical model for linkage analysis of the longitudinal data. The proposed model is a mixed model based on the new Haseman and Elston model and allows several random effects. Specifically, the proposed model includes a random effect for correlation among sib pairs having one sibling in common, and one for the correlation among siblings from the same parents. RESULTS: The proposed model was applied to the analysis of the Genetic Analysis Workshop 13 simulated data set for a quantitative trait of the systolic blood pressure. A simple independence model and two kinds of random effects models yielded good power for detecting linkage for these data sets, while the random effects models performed slightly better than the independence model. Both random effects models showed similar performance. CONCLUSIONS: The proposed models seem not only quite useful in detecting linkage with the longitudinal data for the trait but also quite flexible. They can handle a wide class of correlation structures. Models with a more general class of covariance structure are desirable.

Adult Children↗

PubMed2005

A nonparametric approach to the analysis of longitudinal data via a set of level crossing problems with application to the analysis of microarray time course experiments.

Here we develop a completely nonparametric method for comparing two groups on a set of longitudinal measurements. No assumptions are made about the form of the mean response function, the covariance structure or the distributional form of disturbances around the mean response function. The solution proposed here is based on the realization that every longitudinal data set can also be thought of as a collection of survival data sets where the events of interest are level crossings. The method for testing for differences in the longitudinal measurements then is as follows: for an arbitrarily large set of levels, for each subject determine the first time the subject has an upcrossing and a downcrossing for each level. For each level one then computes the log rank statistic and uses the maximum in absolute value of all these statistics as the test statistic. By permuting group labels we obtain a permutation test of the hypothesis that the joint distribution of the measurements over time does not depend on group membership. Simulations are performed to investigate the power and it is applied to the area that motivated the method-the analysis of microarrays. In this area small sample sizes, few time points and far too many genes to consider genuine gene level longitudinal modeling have created a need for a simple, model free test to screen for interesting features in the data.

Computer Simulation↗

PubMed1998

Longitudinal genetic analysis of menstrual flow, pain, and limitation in a sample of Australian twins.

Genetically informative longitudinal data about menstrual disorders allow us to address the extent to which the same genetic risk mechanisms are operating throughout the reproductive life cycle. We investigate the relative contributions of genes and environment to individual differences in menstrual symptomatology reported at two waves, 8 years apart, of a longitudinal Australian twin study. Twins were questioned in 1980-1982 and 1988-1990 about levels of menstrual pain, flow, and perceived limitation by menses. Longitudinal genetic analysis was based on 728 pairs (466 MZ and 262 DZ) who were regularly menstruating at both survey waves. A bivariate Cholesky model was fitted to the two-wave data separately for flow, pain, and limitation variables. The baseline model comprised common genetic and environmental factors influencing responses at both waves and specific effects influencing only the second-wave response. We also included age as a covariate in the model. Proportions of the longitudinally stable variance in menstrual flow, pain, and limitation attributable to genetic and individual environmental effects were calculated for the best-fitting models. Genetic factors accounted for 39% of the longitudinally stable variation in menstrual flow, 55% for pain, and 77% for limitation. The remaining stable variance was due to individual environmental factors (61, 45, and 23%, respectively). Therefore the stable variance over the 8-year interval was largely environmentally influenced for menstrual flow, was approximately equally determined by genetic and by nonshared environmental influences in the case of pain, and was due almost entirely to genetic influences for limitation by periods. We demonstrate for the first time that the same genetic influences are operative throughout the reproductive life span.

Adolescent↗

PubMed2002

The APO E4 allele and cognition in New Mexico Hispanic elderly.

OBJECTIVE: To determine if the apolipoprotein E E4 (APO E4) allele is associated with cognitive performance in New Mexico Hispanic elderly. METHOD: We performed a cross-sectional survey of 105 community volunteers, aged 60 years and older, born in New Mexico, with both parents of Hispanic descent. Subjects were excluded for medical conditions that could influence cognitive performance. We also performed a longitudinal analysis on 18 participants who were re-tested over a 3-year interval. The main outcome measures for both the cross-sectional and longitudinal analysis were scores on 5 cognitive tests comparing subjects with the E4 allele to those without the E4 allele. RESULTS: The mean age was 69 years, with a range of 60 to 91. For the cross-sectional analysis, there were no significant differences between the 2 groups on the cognitive tests, although subjects with an E4 allele did not perform as well on color trails A (P=.09). In the longitudinal analysis we found that the variability of cognitive test scores tended to be higher in the E4 group on most cognitive measures. The time needed to complete color trails A (indicating slower performance) was significantly greater (P<.05) in the E4 group. For the total recall portion of the Fuld Object Memory test, the E4 group did not perform as well on follow-up (P=.08). CONCLUSION: We found no significant cross-sectional association between the APO E4 allele and cognitive performance. In our longitudinal analysis, the time needed to complete color trails A was significantly greater in the E4 group, and the E4 group did not perform as well on total recall.

Aged↗

PubMed2004

Sensitivity analysis of longitudinal binary data with non-monotone missing values.

This paper highlights the consequences of incomplete observations in the analysis of longitudinal binary data, in particular non-monotone missing data patterns. Sensitivity analysis is advocated and a method is proposed based on a log-linear model. A sensitivity parameter that represents the relationship between the response mechanism and the missing data mechanism is introduced. It is shown that although this parameter is identifiable, its estimation is highly questionable. A far better approach is to consider a range of plausible values and to estimate the parameters of interest conditionally upon each value of the sensitivity parameter. This allows us to assess the sensitivity of study's conclusion to assumptions regarding the missing data mechanism. The method is applied to a randomized clinical trial comparing the efficacy of two treatment regimens in patients with persistent asthma.

Adrenal Cortex Hormones↗

PubMed1991

Longitudinal Gompertzian analysis of ischemic heart disease mortality in the U.S., 1962-1986: a method of demonstrating the deterministic dynamics describing its decline.

Age-adjusted mortality rates for ischemic heart disease (IHD) in the United States from 1962 to 1986 were subjected to longitudinal Gompertzian analysis. Age-adjusted IHD mortality rate distributions between age 40 and 85 years were determined by a variable environmental factor and an extrapolated common intersect point. The environmental factor declined (improved) 3.73-fold for men and 2.07-fold for women in 1986 as compared to 1962. However, the environmental factor in 1986 remained 15.34 fold more conductive to IHD mortality among men than women. The age at the extrapolated common intersect point was 126.7 years for men and 267.4 years for women. Longitudinal Gompertzian analysis of IHD mortality data suggests that IHD will remain a significant cause of mortality for men despite advances in risk factor reduction and medical therapy.

Adult↗

PubMedDate not supplied

An overview of methods for the analysis of longitudinal data.

This paper reviews statistical methods for the analysis of discrete and continuous longitudinal data. The relative merits of longitudinal and cross-sectional studies are discussed. Three approaches, marginal, transition and random effects models, are presented with emphasis on the distinct interpretations of their coefficients in the discrete data case. We review generalized estimating equations for inferences about marginal models. The ideas are illustrated with analyses of a 2 x 2 crossover trial with binary responses and a randomized longitudinal study with a count outcome.

Cross-Sectional Studies↗