About Melk

Melk · ‎02-09-2018

I want to import all the sheets in an excel file with the following conditions: 1) import all sheets without having to specify sheet names (there are too many) 2) import row 6 as the heading (column name) and delete rows 1-5 for each sheet. Each sheet has the same column names. 3) Preferably wan to append each sheet to get 1 dataset. Again, each sheet as the same column names starting on row 6. Anyone have any tips to code this import?

Melk · ‎01-31-2018

I tried alphaqt = 0.05 but it didnt work.

Melk · ‎01-26-2018

I am running a 2 sample wilcoxon and also supplementing my p-value with with medians using proc means. However, the number of obs in each are different: proc means reports I have 3 in my class variable whereas npar1way reports I have 2. What can be the reason for this? proc means data=x median; where group = "A"; class sub; var change; run; proc npar1way data=x wilcoxon; where group = "A"; class sub; var change; exact; run;

Melk · ‎01-11-2018

Added, just A or B

Melk · ‎01-10-2018

I would like to create a graph with age as my x axis and subject ID as my Y axis, grouped by treatment group. I want the markers to represent the subject visit at each age and a line to connect across to all visits, only by ID. How can I do this? Sample data set: ID VISIT AGE Y TX 1 1 40 200.4 A 1 2 43 144.4 A 1 3 45 106.3 A 2 1 36 120.6 B 2 2 39 106.8 B 2 3 41 101.1 B

Melk · ‎01-10-2018

I have an estimate statement time 1 time*group 1 0 0; Time is measured in days in my dataset. I want to estimate the progression of the outcome variable by week or month instead of day. If I replace the time 1 with time 7 or time 30, will that give me a rate by week/month?

Melk · ‎01-10-2018

I looked at the group by time interaction in the model and because it was NS and because it was not part of the research question, I removed it to not overparameterize the small sample size. Hmm

Melk · ‎01-10-2018

I only have 10 subjects in each of my group so about 20 eyes per group, this is the only model I got which did not give me a G matrix error. Not sure if there are any other tips for small samples sizes of this design.

Melk · ‎01-05-2018

I am running a proc mixed with 1 fixed treatment effect and a random nested effect of eye within ID. proc mixed data = dat; class id tx eye; model y= tx/solution; random time/ subject=eye(id); lsmeans tx / pdiff adjust=tukey; run; My random statement kind of confuses me - I have a random effect of eye within id, over continuous time. How does this affect my interpretation of my tx effect?

Melk · ‎01-05-2018

They didnt receive a different treatment in each eye. I thought about doing that, but due to the small sample size, I thought it would be better to model both eyes as nested within ID. I read that the output for this would be interpreted as the average between each eye. Is that correct?

Melk · ‎01-03-2018

There is no baseline in the usual sense where we have some sort of intervention. I just have 3 datapoints across time. I would like to use time as continous because they are not identical across patients. I also have a small sample, so I want to minimize the number of parameters as much as possible. Group should not be random, you are right. Based on your reference, I came up with: proc mixed data = dat; class subject group eye; model y= group/solution; random int time/ subject=eye(subject); lsmeans group/ pdiff adjust=tukey; run; But I am still getting a G matrix not positive definite error. Not sure what to do?

Melk · ‎01-02-2018

What do you think about losing one of my nested random effects?

Melk · ‎12-19-2017

I am running a mixed model for a small sample with 3 groups - 10 in each group. I am interested in whether the outcome variable (continuous) mean is significantly different by group. I have longitudinal data on 3 timepoints. I also have data for right and left eye. How should i model my random effects with such a small sample? I am getting a convergence error with the below code: proc mixed data = dat; class subject group eye; model y= group /solution; random group /sub = subject(visit eye) type=un; lsmeans group / pdiff adjust=tukey; run;

Melk · ‎12-15-2017

I think you are right, I only care about observations that start with my diagnosis of interest, I suppose in the case of a 0 then a 0 then a 1, I would then throw out the first 2 observations though.

Melk · ‎12-14-2017

I have a longitudinal dataset (assuming it is already sorted by increasing time): ID DX 1 0 2 1 2 0 3 2 4 0 4 1 4 2 5 0 I want to keep the observations in the dataset where DX is 1 or 2. But, if DX is 0, I only want to throw it out if (1) it is the only record for that ID or (2) if it is the first observation for that ID and is followed by a DX of 1 or 2.For the example above, it would look like: ID DX 2 1 2 0 3 2 4 1 4 2 How can I do this? Thank you!

Online Status	Offline
Date Last Visited	‎07-14-2020 04:02 PM

Re: Automated variable selection

Re: Automated variable selection

Automated variable selection

Identify dates in close proximity by group in longitudinal data

datalabels and seglabels in sgplot

Identify the best predictor of a count outcome

Identifying non-exact duplicates in the same dataset

Multinomial models for clustered data using GLIMMIX

Re: Modelling multilevel data

Re: Modelling multilevel data

Re: Automated variable selection

Re: Doing a SAS procedure within an array

Re: Transposing many responses to columns with binary response

Re: Write one line of code to delete everything in the WORK directory?

Re: How do I adjust for clustered data in logistic regression?

Re: Is a sample size of 5 enough to run a glimmix model?

import all sheets in excel file

how do I get 95% confidence intervals for survival estimates in the li...

Different N obs between proc means and proc npar1way

Re: How to plot by ID by VISIT across age

How to plot by ID by VISIT across age

Change units of measurement in estimate statement in proc mixed

Re: How to interpret a nested random effet in proc mixed

Re: How to interpret a nested random effet in proc mixed

How to interpret a nested random effet in proc mixed

Re: modeling right and left eye in a mixed model with small sample siz...

Re: modeling right and left eye in a mixed model with small sample siz...

Re: modeling right and left eye in a mixed model with small sample siz...

modeling right and left eye in a mixed model with small sample size

Re: Keeping observations by longidutinal data techniques

Keeping observations by longidutinal data techniques