This article presents a within-individual examination of the effects of work engagement on the family domain. A total of 125 employees were asked to respond to daily surveys both at work and at hom...

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Why Do Employees Have Better Family Lives When They Are Highly Engaged at Work

Intensive longitudinal data are defined as repeated observations that cover more than the usual three or four observation points in time (in chapter 3 of this book, intensive data also include “massively multivariate” data; p. 63). Most methods of statistics with which the average user is familiar have no problems handling short series of observations. These methods include, for example, analysis of variance (ANOVA), log-linear modeling (LLM), and structural equation modeling (SEM). Consider, however, a series of 20 measures. Here, ANOVA, LLM, and SEM methods can become unwieldy, and models for intensive longitudinal data are needed. The book edited by Walls and Schafer covers two broad topics. First, it presents methods for the statistical analysis of such data. Based on this alone, the book is useful and can be recommended. Second, the book also contains a good number of examples of topics that can only be addressed when intensive longitudinal data are available. An example of such a topic concerns the “complexity and variety of individual trajectories and the need to move beyond simple time-graded effects” (p. xiv). Just imagine the number of observation points and respondents needed for the comparison of five developmental groups that differ in the point in time in which they change acceleration in a growth curve. Using the typical design with just three or four data waves, the trajectories of these groups can be compared in only a rudimentary fashion. The compilation of sample cases makes this book even more valuable.

“Models for Intensive Longitudinal Data.” Theodore A. Walls & Joseph L. Schafer (Eds.). Oxford, UK: Oxford University Press, 2006, 288 pages, $65.00 (hardcover)

Anna Lorys

Papers

Establishing Balance: An Experience Sampling Methodological Study of the Work-Life Interface