Methods: Secondary data analyses were conducted using wave 3 (2005-2006) data. Children (birth-four and 10-14) with a female caregiver constitute the sample. An EFA was conducted to assess the underlying factor structure and refine the item pool to determine if all six items of the financial strain measure represent the financial strain construct. Data were analyzed as ordered-categorical using the WLSMV estimator. Each construct was analyzed and fit indices were examined to determine if the model fit the data. The chi-square test of model fit was used to determine the goodness of fit between the sample covariance matrix and the restricted covariance matrix as well as the comparative fit index (CFI), the Tucker-Lewis index (TLI), and the root mean square error of approximation (RMSEA).
Results: Exactly 886 observations were used to run the EFA. Results indicate a RMSEA value of .096, higher than the .08 cutoff value. The SRMR was .035, below the recommended value of .06. The CFI (.983) and TLI (.972) fell within the cutoff range of >.95 but the chi-square test results were significant (2= 55.197, df = 9, p< .001), indicating possible model misfit. The fit indices for the measure with two factors indicate a RMSEA value of .081, just above the .08 cutoff value. The SRMR was .015, well under the .06 cutoff value. The CFI (.997) and TLI (.989) fell within the cutoff range of >.95 and the chi-square test results were significant (2= 12.425, df = 4, p=.0145), indicating this model is a good fit to the data.
Using the EFA results as a guide, another sample of 881 respondents was drawn to conduct the CFA. Results testing the one-factor measure in the CFA indicated a RMSEA of .092, above the set .08 cutoff value, which is not favorable. The CFI (.984) and TLI (.973) were above the .95 cutoff value indicating a positive result. Further, the chi-square result was significant (2=50.532, df = 8, p<.001), revealing the model should be rejected to avoid possible bias.
Conclusions and Implications: Results of the EFA and CFA are an important step towards identifying the factor structure of a financial strain measure. This measure could be used with a different sample population and an EFA and CFA conducted to determine whether or not the factor structure results found in this study hold across different sample populations. Future analyses on the factor structure of this financial strain measure could move researchers towards a more common measure and ultimately operationalization of the financial strain construct.