Logistic regression model-building strategies for predicting regular mammography screening adherence among uninsured immigrant women
نویسندگان
چکیده
While one-time mammography screening rates have improved, repeat-screening rates have not followed this trend. Little is known about those factors that help sustain the regular use of mammography over time, especially among low-income, uninsured immigrant women. We utilized model-building strategies using the SAS LOGISTIC procedure to find a set of candidate logistic regression models that included a candidate set of predictors for repeat-screening mammography among 562 uninsured immigrant women who participated in the California No-Cost Screening Program (CANCSP). Rationale for the strategies and procedures used is given and limitations are discussed.
منابع مشابه
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