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Then, compose a 1- to 2-paragraph analysis in APA format including discussion of if the predictive relationship is statistically significant and the odds ratio and what it means.īe sure to include your data output with your analysis We emphasize that the Wald test should be used to match a typically used coefficient significance testing. The Wald test is used as the basis for computations. Use SPSS to answer the research question you constructed (What is the relationship between the final exam scores and gender, that is, males and females participants?). This program computes power, sample size, or minimum detectable odds ratio (OR) for logistic regression with a single binary covariate or two covariates and their interaction.
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You would still score about 70% of tumors as malignant because about 70% of tumors have scores above the value of 10, the first type of probability. If you wanted to use a cutoff to map probabilities into yes/no predictions, then 10 could be a reasonable choice of cutoff even though it maps to the 0.5 probability cutoff in your model of that second type of probability. So a tumor with a value of 10 has a probability of 0.5 of being malignant. That's a model of the second type of probability: If I know the value of the biomarker, what's the probability that the tumor is malignant?Īs an extreme example, say that all tumors with biomarker values 11 were malignant, and the few tumors with values between 9 and 11 had a 50/50 chance of being malignant.
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There may be no simple relation between these two types of probabilities.Ī logistic regression model is a model of probabilities, as this answer among others on this site emphasizes. That depends on the quality of your biomarker and your probability model. The second is the probability, after you've run the test to get the biomarker value, that a tumor with a particular biomarker value is malignant. One is the probability, before you've run any tests, that someone with such a tumor has the malignant type: the 70% prevalence of the malignant form for this type of tumor. It's easy to get confused between the two different types of probabilities that you face in this type of study.