Multivariate methods for binary longitudinal data with heterogeneous correlation over time

1992 ◽  
Vol 11 (14-15) ◽  
pp. 1915-1928 ◽  
Author(s):  
B. Rosner
Keyword(s):  
Longitudinal Data ◽  
Multivariate Methods ◽  
Binary Longitudinal Data ◽  
Over Time

Coping with longitudinal data in research on developmental psychopathology

2006 ◽  
Vol 30 (1) ◽  
pp. 20-25 ◽  
Author(s):  
David A. Cole
Keyword(s):  
Data Collection ◽  
Longitudinal Data ◽  
Developmental Psychopathology ◽  
Careful Consideration ◽  
Two Dimensions ◽  
The Other ◽  
Outcome Variable ◽  
The Third ◽  
Data Analytic ◽  
Over Time

Many outcome variables in developmental psychopathology research are highly stable over time. In conventional longitudinal data analytic approaches such as multiple regression, controlling for prior levels of the outcome variable often yields little (if any) reliable variance in the dependent variable for putative predictors to explain. Three strategies for coping with this problem are described. One involves focusing on developmental periods of transition, in which the outcome of interest may be less stable. A second is to give careful consideration to the amount of time allowed to elapse between waves of data collection. The third is to consider trait-state-occasion models that partition the outcome variable into two dimensions: one entirely stable and trait-like, the other less stable and subject to occasion-specific fluctuations.

The analysis of binary longitudinal data with time-dependent covariates

2012 ◽  
Vol 31 (10) ◽  
pp. 931-948 ◽  
Author(s):  
Matthew W. Guerra ◽  
Justine Shults ◽  
Jay Amsterdam ◽  
Thomas Ten-Have
Keyword(s):  
Longitudinal Data ◽  
Time Dependent ◽  
Binary Longitudinal Data ◽  
Time Dependent Covariates

Neighborhood Firearm Victimization Rates and Social Capital Over Time

2015 ◽  
Vol 30 (1) ◽  
pp. 81-96 ◽  
Author(s):  
Justin C. Medina
Keyword(s):  
Social Capital ◽  
Longitudinal Data ◽  
Theoretical Framework ◽  
Policy Planning ◽  
Regression Analyses ◽  
Neighborhood Social Capital ◽  
The Relationship ◽  
The U.S ◽  
Over Time ◽  
Victimization Rates

Distribution of firearm victimization is not equal within cities. Victimization can persistently concentrate in a small number of neighborhoods, while others experience very little violence. Theorists have pointed to one possible explanation as the ability of groups to control violence using social capital. Researchers have shown this association at the U.S. county, state, and national levels. Few studies, however, have examined the relationship between neighborhood social capital and violence over time. This study uses longitudinal data to ask whether neighborhood social capital both predicts and is influenced by firearm victimization over 3 years in Philadelphia. The results of several regression analyses suggest that trusting others and firearm victimization are inversely related over time. Implications for neighborhood policy planning and social capital as a theoretical framework are discussed.

Differential Aging: An Exploratory Approach Using Cluster Analysis

1984 ◽  
Vol 18 (2) ◽  
pp. 141-157 ◽  
Author(s):  
Graeme Ford ◽  
Rex Taylor
Keyword(s):  
Cluster Analysis ◽  
Longitudinal Data ◽  
Random Sample ◽  
Successful Aging ◽  
Elderly Population ◽  
Structural Data ◽  
Exploratory Approach ◽  
Aging Well ◽  
Well Elderly ◽  
Over Time

This article uses cluster analysis to identify different patterns of personal resources within a random sample of the well, elderly population. Ten such patterns or natural groupings are identified and their implications for coping and successful aging are discussed. It is apparent that there are a number of ways both of aging well and aging badly, and that these patterns cannot be predicted solely on the basis of structural data. The article poses a number of questions on the performance of cluster members over time and draws attention to the importance of longitudinal data.

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