Dear friends of Statalist, good morning.
I am a doctor from Argentina (MD, PhD, MSC), and I work at the Hospital Italiano in Buenos Aires.
I am investigating MIMIC (Multiple IndicatorsMultiple Causes) models since with them I can do regressions, including factors (made up of several items), and the observed variables (glycemia, cholesterol, blood pressure, etc.). All together.
I work with RStudio, and I have the Probit coefficients as a result. Since the interpretation of Probit coefficients is not very "intuitive", think about helping the reader with these two methodologies:
1) I am considering, in addition to the Probit regression result, offering the reader an estimate of the odds ratio, first multiplying by 1.7 to obtain the logit coefficients (Scott Long, 2014), and then applying the exponential function (the natural anti-logarithm ), to the estimated value of the logit coefficient, to calculate the odds ratio.
2) Additionally, with STATA, calculate the predicted probabilities of the independent variable that interests me the most, with the command:
“margins , at (variable =(())) vsquish”.
Where I can place, as adjustment variables, the other observed variables, and also the variables or items that make up the factors (since I cannot directly include the factors, or latent variables).
Does it seem appropriate to you, to complement the results?
I am a doctor from Argentina (MD, PhD, MSC), and I work at the Hospital Italiano in Buenos Aires.
I am investigating MIMIC (Multiple IndicatorsMultiple Causes) models since with them I can do regressions, including factors (made up of several items), and the observed variables (glycemia, cholesterol, blood pressure, etc.). All together.
I work with RStudio, and I have the Probit coefficients as a result. Since the interpretation of Probit coefficients is not very "intuitive", think about helping the reader with these two methodologies:
1) I am considering, in addition to the Probit regression result, offering the reader an estimate of the odds ratio, first multiplying by 1.7 to obtain the logit coefficients (Scott Long, 2014), and then applying the exponential function (the natural anti-logarithm ), to the estimated value of the logit coefficient, to calculate the odds ratio.
2) Additionally, with STATA, calculate the predicted probabilities of the independent variable that interests me the most, with the command:
“margins , at (variable =(())) vsquish”.
Where I can place, as adjustment variables, the other observed variables, and also the variables or items that make up the factors (since I cannot directly include the factors, or latent variables).
Does it seem appropriate to you, to complement the results?
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