Academic journal article Journal of Marriage and Family

Are Divorce Studies Trustworthy? the Effects of Survey Nonresponse and Response Errors

Academic journal article Journal of Marriage and Family

Are Divorce Studies Trustworthy? the Effects of Survey Nonresponse and Response Errors

Article excerpt

Researchers rely on relationship data to measure the multifaceted nature of families. This article speaks to relationship data quality by examining the ramifications of different types of error on divorce estimates, models predicting divorce behavior, and models employing divorce as a predictor. Comparing matched survey and divorce certificate information from the 1995 Life Events and Satisfaction Study (N = 1,811) showed that nonresponse error is responsible for the majority of the error in divorce data. Misreporting the divorce event was rare, and more than two thirds of respondents provided a divorce date within 6 months of the actual date. Nevertheless, divorce date error attenuated effects of time since divorce on outcomes. Gender, child custody, marital history, and education were associated with divorce error.

Key Words: divorce, marriage and close relationships, measurement, panel studies, relationship processes, survey research.

A large proportion of research on families relies on respondents reporting their relationship history. This information may come from questions about current marital status or whether the respondent has ever been in particular relationship types, or from the completion of full relationship histories. As families have increased in complexity over the past several decades, research on the number and timing of relationship entries and exits has increased substantially (Milardo, 2000), and some suggest that models are still not complex enough, as a result of poor measurement of timing, type, and number of relationships (Hofferth & Casper, 2007). To date, research on the quality of relationship information is limited (Bumpass & Raley, 2007; Knab & McLanahan, 2007; Pollard & Harris, 2007). Understanding the extent that people misreport relationship events and dates is important because data quality determines the likelihood of models being misspecified or temporally incongruent and results biased. This article addresses relationship data quality by examining survey-gathered divorce information.

During the past several decades, social scientists have studied the causes and consequences of divorce considerably, often using survey-collected divorce data (Amato, 2000; Coleman, Ganong, & Fine, 2000). Because of their versatility, survey-collected divorce data are particularly important to scholars, and their significance has only increased with Vital Statistics no longer compiling divorce information (Bramlett & Mosher, 2002). Survey-collected data may be used to estimate the number of divorces, population divorce rates, or hazard rates of divorce, and by adding independent variables to hazard estimates, scholars can produce models of the predictors of divorce and divorce timing. Analogously, divorce experience and timing are often used as predictors of many dependent variables in studies of remarriage, mental health, economic outcomes, and child well-being - fields that have seen tremendous research attention over the past two decades. In fact, in the 1990s alone, more than 850 articles were published on stepfamilies, which by definition require some measure of divorce experience, although not all used survey-collected data (Coleman et al., 2000).

Previous research also suggests surveygathered divorce data are sometimes very inaccurate. Depending on the study, scholars have found that the survey estimates of divorce are between 8% and 25% less than the Vital Statistics figures (Bumpass, Castro-Martin, & Sweet, 1991; McCarthy, Pendleton, & Cherlin, 1989; Preston & McDonald, 1979; O'Connell, 2007). Thus, assuming that the Vital Statistics tallies are correct, survey data on divorce are decidedly unreliable and imprecise. Scholars have hypothesized the sources of the discrepancies between the Vital Statistics data and survey data, with some suggesting deliberate misreporting of information by divorced respondents, and others suggesting higher refusal rates for divorced individuals. …

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