A comparison of sequence analysis, latent class growth models, and multi-state event history models for studying partnership transitions
نویسندگان
چکیده
This paper qualitatively compares and contrasts three methods that are useful for life course researchers; the more widely used sequence analysis, and the promising but less often applied latent class growth models, and multi-state event history models. The strengths and weaknesses of each method are highlighted by applying them to the same empirical problem. Using data from the Norwegian Generations and Gender Survey, changes in the partnership status of women born between 1955 and 1964 are modelled, with education as the primary covariate of interest. We show that latent class growth models and multi-state event history models are a useful addition to life course researchers’ methodological toolkit and that these methods can address certain research questions better than the more commonly applied sequence analysis or simple event history analysis.
منابع مشابه
Longitudinal methods for life course research : A comparison of sequence analysis , latent class growth models , and multistate event history models for studying partnership transitions
This paper compares and contrasts three methods that are useful for life course researchers; the more widely used sequence analysis, the promising but less often applied latent class growth models, and multistate event history models. The strengths and weaknesses of each method are highlighted by applying them to the same empirical problem. Using data from the Norwegian Generations and Gender S...
متن کاملMultilevel Models for Longitudinal Data
Repeated measures and repeated events data have a hierarchical structure which can be analysed using multilevel models. A growth curve model is an example of a multilevel random coefficients model, while a discrete-time event history model for recurrent events can be fitted as a multilevel logistic regression model. The paper describes extensions to the basic growth curve model to handle autoco...
متن کاملAn application of Measurement error evaluation using latent class analysis
Latent class analysis (LCA) is a method of evaluating non sampling errors, especially measurement error in categorical data. Biemer (2011) introduced four latent class modeling approaches: probability model parameterization, log linear model, modified path model, and graphical model using path diagrams. These models are interchangeable. Latent class probability models express l...
متن کاملUsing multivariate generalized linear latent variable models to measure the difference in event count for stranded marine animals
BACKGROUND AND OBJECTIVES: The classification of marine animals as protected species makes data and information on them to be very important. Therefore, this led to the need to retrieve and understand the data on the event counts for stranded marine animals based on location emergence, number of individuals, behavior, and threats to their presence. Whales are g...
متن کاملThe Comparison of Two Models for Evaluation of Pre-internship Comprehensive Test: Classical and Latent Trait
Introduction: Despite the widespread use of pre-internship comprehensive test and its importance in medical students’ assessment, there is a paucity of the studies that can provide a systematic psychometric analysis of the items of this test. Thus, the present study sought to assess March 2011 pre-internship test using classical and latent trait models and compare their results. Methods: In th...
متن کامل