About LucyB

LucyB · ‎05-09-2017

Hello again! What if we were interested in whether there is significant differences between the regressions and not necessarily the slopes themselves? We want to be able to conclude that increased heartbeat is more suppressed post as compared to pre, but we do not necessarily want to make a conclusion about differences in slope (the varying levels of "drink" are actually not important). THank you!

LucyB · ‎05-04-2017

I have a category in my x axis and I am unsure what type of graph would be most appropriate. My Y axis would be a count per year. I only end up with 8 "per year categories". They are in fractions like 0.25, 0.50, 0.75, 1, 1.5, etc. I have 200 patients. What would be the best way to depict this?

LucyB · ‎04-28-2017

Thank you, so this plots the probabilities for 2 of my predictors but fixes the value for my 3rd. I want to compare across all 3 somehow..

LucyB · ‎04-28-2017

I am running a proc logistic and am looking specifically at a 3 way interaction. Here is some descriptives on my data: Outcome: mortality (y/n) Var 1: gender (M/F) Var 2: dichotomous lab value (above/ below certain critical cutoff- y/n) Var 3: second dichotomous lab value (above/ below certain critical cutoff- y/n) I am looking to see who is more at risk for the mortality outcome and have included an interaction for these terms in the model. My interaction p-value is not significant, but I want to report directions. Since I have 3 dichotomous variables, what would be the best way to present this (preferably graphically) in regards to who is more likely to experience mortality?

LucyB · ‎04-11-2017

Due to problems with non-normal residuals, I have run a rank-based ANOVA on my outcome variable (continuous). My indepedent variable is binary (Yes/No). I have 1 continous covariate in the model. When I look at median values for each group - they are quite different (10 vs. 97) - this is a score outcome. IQR is quite large as well. When I run my rank based ANOVA - the p value for the group is highly insignificant- both in the crude and adjusted models. How is this possible? The medians are so different.

LucyB · ‎04-06-2017

I have some exam data for some middle school students, with 2 continuous outcomes i am interested in looking at (1) exam score (2) time it takes to complete the exam Is it possible to combine these to 1 meaningful outcome variable (they have different scales and better is higher for score and lower for the time)? I want to compare the effect of a predictor and also look at differences in this association by county.

LucyB · ‎04-05-2017

Yes- the standardization itself did not address the collinearity, but because of the standardization, a composite can be calculated, which will address the collinearity from my understanding.

LucyB · ‎04-05-2017

but doesnt it still address multicollinearity?

LucyB · ‎04-05-2017

Well from what I remember from a course, if you have multicollinearity among some covariates (these are questionairres), you can cover them to Z scores, and then average them to be 1 variable. is this not correct?

LucyB · ‎04-04-2017

I am running a multiple linear regression model and I have 8 covariates, 4 of them are highly correlated (r>0.7). So I created z scores and then created a composite. When I re-ran the model with this composite, my predictor p-value became significantly larger and my R2 went down. Why is this happening? I thought p-values decreased after accounting for multicollinearity?

LucyB · ‎04-03-2017

which one? I have not come across a free e-course

LucyB · ‎04-01-2017

Can anyone recommend a comprehensive book going through most of the important statistical methods with SAS examples?

LucyB · ‎04-01-2017

what exactly is the significance of the sample group?

LucyB · ‎03-31-2017

I have a mortality outcome (yes/no) and a categorical predictor (white,hispanic,black, asian) I am running a logistic regression on. I would like to see if some other factors, like age, type of med, etc. are risk factors for the death outcome. Would it be best to add to the model in a stepwise fashion? Would this answer my question, or would it be an interaction?

LucyB · ‎03-30-2017

but does this still not make the same assumptions? my outcome is skewed.

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Re: Pre-Post data with exposure-varying intervals

Which type of graphic is appropriate?

Re: Interaction visualization in PROC LOGISTIC

Interaction visualization in PROC LOGISTIC

rank based ancova

Creating a meaninful composite outcome

Re: My p-value increases when I account for multicollinearity in my ML...

Re: My p-value increases when I account for multicollinearity in my ML...

Re: My p-value increases when I account for multicollinearity in my ML...

My p-value increases when I account for multicollinearity in my MLR?

Re: Which type of graphic is appropriate?

Re: Interaction visualization in PROC LOGISTIC

Re: Interaction visualization in PROC LOGISTIC

Re: Creating a meaninful composite outcome

Re: My p-value increases when I account for multicollinearity in my ML...

Repeated Measure ANOVA on RAnks

Re: Pre-Post data with exposure-varying intervals

Which type of graphic is appropriate?

Re: Interaction visualization in PROC LOGISTIC

Interaction visualization in PROC LOGISTIC

rank based ancova

Creating a meaninful composite outcome

Re: My p-value increases when I account for multicollinearity in my ML...

Re: My p-value increases when I account for multicollinearity in my ML...

Re: My p-value increases when I account for multicollinearity in my ML...

My p-value increases when I account for multicollinearity in my MLR?

Re: Comprehensive SAS book recommendations

Comprehensive SAS book recommendations

Re: which statistical test to choose?

risk factors for logistic outcome

Re: Repeated Measure ANOVA on RAnks