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Introduction
Current institution
Publications
Publications (2)
Persistent pulmonary hypertension of the newborn (PPHN) is associated with high morbidity and mortality. This study evaluated clinical outcomes in PPHN in relation to echocardiographic (EC) markers, score of neonatal acute physiology, perinatal extension, version II (SNAPPE II) scores, inotropic agent use, and the amount of fluid received as boluse...
We describe the unusual case of a 9-month-old Caucasian girl with a retropharyngeal abscess secondary to a mastoid abscess who presented with torticollis. The retropharyngeal abscess was caused by pus from the mastoid abscess tracking down under the petrous part of the temporal bone to reach the retropharyngeal space via the fossa of Rosenmüller. W...
Questions
Questions (2)
I'm trying to calculate attributable risk of a risk factor for a disease Adjusting for related risks Using R -" attribrisk package"
we managed to get AR value and CI how ever we couldn't get the p value for the estimate / value .. just want to know what else I need to include in the "attribrisk package"
appreciate the help please !!!
thanks
Say for eg we have a bigger( about 1/2 million observations) data set on birth weights .
Depended variable being a low birth weight a dichotomous variable.
Independent variable-is different age group mothers ( say 4 groups 15-25 26-30 31-44, 45-59).
confounding variables :1) marriage 2) financial status 3) got insurance or no. etc..all of them are dichotomous variables (yes /no
want to know the association by calculating an Odds ratio. by constructing a model and analyzing via multi logistic regression. model ... say as below
LBW(dependent var))= b +x1(mothers age group/independent var )b1+x2(marriage/confounding var 1) b2+.confond var2 B3+.........etc
when I ran a SAS code including all variables with an aim to delete the confounding effect on my dependent var ..what is the best strategy to do..
1)is it stratification or controlling or adjusting ..
2)what is the difference between those 3/any of those are same.
3)how dos those 3 procedures/methods work and effect the OR of dependent variable
I'm sorry I'm new to statistics trying to understand basic concepts..
