Abstract
In this chapter we are going to introduce the methods that we will use to empirically answer our research questions. The objective is to provide a brief overview of our methodological choices by expounding on possible alternatives, and to provide the background information necessary for understanding the results presented in the subsequent chapters. We begin by determining the measurement level of ordinal-level variables and the resulting choices for bivariate statistics before specifically addressing the two main methods used, regression models and structural equation models. All statistical analysis presented in this volume was performed using the software Stata 12.
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Notes
- 1.
Some researchers may be tempted to collapse categories in order to artificially inflate the gamma coefficient.
- 2.
The Self-Assessed Measure fulfills this criterion, but not the Perceived and the Objective Measures.
- 3.
exp(b) = odds ratios, subsequently abbreviated as OR.
- 4.
According to Hoyle (1994), factor analysis can be considered a special case of the general structural equation model.
- 5.
The pathways between two variables can either be left free to vary because the objective is to measure the relationship between the two, or it can be fixed, usually based on the estimations found in previous studies.
- 6.
If the model contains k observed variables, we have {k ∗(k + 1)}/2 pieces of information. A just-identified model (with 0 degrees of freedom) can be fitted but it cannot be tested by any measure of goodness of fit, which is why it should be avoided (Acock 2013, p. 43).
- 7.
In the case of the VLV survey, when we refer to the ‘total population’ we do not refer to all of Switzerland since the five sampling regions (cantons and parts of cantons) have not themselves been chosen in the context of a sampling process, rather, we refer to the total population aged 65 and older in all five sampling regions taken together. Because of the selection criteria described in ‘Population surveyed’ we believe that the survey is somewhat representative of the Swiss situation though not in a strictly speaking statistical sense.
- 8.
The method for calculating the sample weights was decided collectively by the researchers involved in the VLV study.
- 9.
The assumption that model errors are independent with mean 0 and homogeneous variance (Kleinbaum et al. 2013).
- 10.
Pseudo Maximum Likelihood (PML) for linearization estimation of asymptotic covariance consists of two components: (1) replacing sample covariances by weighted sample covariances, and (2) replacing inverse Fisher information with a sandwich estimator of variance (Bollen et al. 2013, p. 1236). As alternative approaches a variety of resampling methods (jackknife repeated replication, balanced repeated replication, and bootstrapping) have been introduced in the estimation of SEM with complex survey data (Stapleton 2008).
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Henke, J. (2020). Analytical Methods. In: Revisiting Economic Vulnerability in Old Age. Life Course Research and Social Policies, vol 11. Springer, Cham. https://doi.org/10.1007/978-3-030-36323-9_8
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