Abstract
This chapter begins a series of three which present the quantitative analyses with the National Violence Against Women Survey (1995–96) in the US, the Health, Well-being, and Safety of Women in Germany survey (2003–04), and the Survey of Everyday Safety in Norway (2003–04). To begin, the chapter provides a descriptive overview of the US, German, and Norwegian samples based on the variables of interest. Following this are the results of the bivariate analyses determining the initial relationships and their significance between social position, IPV exposure, health outcomes, and the sociodemographic control variables. These analyses offer a clearer picture of the composition of each of the samples and provide the first clues toward answering this book’s research questions. The chapter concludes with a brief summary of the key similarities and differences across countries and the remaining puzzles to be solved by the multiple regression analyses in Chaps. 7 and 8.
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- 1.
Approximately $38,415 and $21,973 before taxes, respectively, in 2015 currency (US Bureau of Labor Statistics n.d.).
- 2.
Approximately €45,812 and €21,523 before taxes, respectively, in 2015 currency (European Central Bank 2015).
- 3.
Approximately €20,858 and €8989 after taxes, respectively, in 2015 currency (European Central Bank 2015).
- 4.
- 5.
Given the differences in time frames and amounts used to measure alcohol consumption across surveys (see Chap. 5), caution should be taken in ascribing too much meaning regarding differences in this indicator across countries.
- 6.
Based on tests of normality, it was determined that all interval variables (i.e., age, number of children, income levels, years of education, and number of mental health complaints) violated the assumption of normality. The statistical tests described here and in Chaps. 7 and 8 take this into account.
- 7.
A number of different correlation tests (i.e., Pearson’s product moment correlation, point biserial correlations, Spearman’s rank order, and Cramér’s V) and independence tests (i.e., Kruskal–Wallis, Pearson chi-square, t tests) were utilized according to types of variables tested (e.g., interval, ordinal, dichotomous). Precise information on these tests, as well as explanations of the interpretation of the correlation coefficients, can be found in Chap. 5.
- 8.
References
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Larsen, M.M. (2016). First Insights into the Relationships Between Social Position, IPV Exposure, and Health Outcomes. In: Health Inequities Related to Intimate Partner Violence Against Women. Social Disparities in Health and Health Care. Springer, Cham. https://doi.org/10.1007/978-3-319-29565-7_6
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