The Finishing Touches
Mahita v -
Welcome back to week 8 of my senior blog posts. This week I finished up my analysis for both of my survey themes. I also went back and conducted chi-square tests to clarify the results of my logistic regression. I used a Chi-Square Test of Independence to examine whether a patient’s race was associated with each of the insurance-related variables in breast cancer care. Since both variables were categorical, this test helped me determine if the disparities I observed were statistically significant — not just random chance.
I researched what would be the best way to conduct the tests, and discovered that I could use the scipy and researchpy libraries in python.
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crosstab = pd.crosstab(df_insurance[“race”], df_insurance[“insurance_acceptance”])
Crosstab
stats.chi2_contingency(crosstab)
crosstab, test_results, expected = rp.crosstab(df_insurance[“race”], df_insurance[“insurance_acceptance”],
test= “chi-square”,
expected_freqs= True,
prop= “cell”)
crosstab
test_results
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I found that there was a statistically significant difference for all the questions except insurance acceptance (which matches the results from the logistic regression). The code also gave me a value for Cramer’s V – a statistical measure that tells us the strength of the association between two categorical variables ranging from 0 to 1. For instance, the Cramer’s V for the copay question was 0.0537 which suggests a minimal influence of race and ability to afford the copay. This statistical measure helps me understand the extent of the statistical significance. However, I’m planning to have a meeting with my project advisor to look over the results as well.
Other than that, I also finished creating my data tables and starting my slides for my presentation. Next week, I will be fully focused on writing my final research paper and practicing my presentation.
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