topic Re: Trend of a continuous variable in a repeated model in Statistical Procedures

Trend of a continuous variable in a repeated model

tka726 — Mon, 09 Aug 2021 17:30:06 GMT

I am trying to see if there is a trend in a continuous lab value over time. There are 3 timepoints (1=baseline, 2=month 1, 3=month 2). I structured the data such that each patient has 3 records. Most patients have data for all 3 timepoints, but not all.

Is a mixed model appropriate, with repeated time? Or do I use proc reg?

I am relatively new with proc mixed; this is the mixed model I currently have.

proc mixed data=lab covtest;

class time ptno;

model labval = time;

repeated time/subject=ptno type=un;

lsmeans time / cl pdiff adjust=tukey;

ods output LSMeans=lsmeans1;

run;

Type 3 Tests of Fixed Effects
Effect Num DF Den DF F Value Pr > F
time 2 207 137.04 <.0001

Do I use the type 3 tests of fixed effects to determine if there is a trend over time?

IF I want to see the differences between any 2 timepoints, should I use the p-values from the differences of least square means section, or should I do paired t-tests/wilcoxon signed rank?

Re: Trend of a continuous variable in a repeated model

SteveDenham — Mon, 09 Aug 2021 19:24:16 GMT

EDIT: I forgot to say that your PROC MIXED approach is quite good. I wouldn't shift to REG. The Type3 tests are whether at least one time point mean differs from all the rest. That may not be a trend, so...

If you want to look at a trend in time, use an LSMESTIMATE statement.

lsmestimate 'linear time' time -1 0 1;
lsmestimate 'quadratic time' time 1 -2 1;

Note that with 3 time points, for linear time the middle time point has no effect, which is why looking at the quadratic time (or deviation from linearity) is useful.

SteveDenham

Re: Trend of a continuous variable in a repeated model

tka726 — Mon, 09 Aug 2021 19:40:08 GMT

Thank you!
The p-value for 'linear time' and 'quadratic time' are both significant. I understand that the significant p-value for linear time means that there is a difference in lab value between time 1 and time 3, but I don't exactly understand what the significant p-value for quadratic time means...?

Re: Trend of a continuous variable in a repeated model

SteveDenham — Wed, 11 Aug 2021 14:41:12 GMT

Here is an interpretation: Significant linear means that a straight line fit through the 3 means will have a slope that is significantly different from 0. Significant quadratic tests whether there is a significant deviation from linearity in the means - that while a straight line fits, there is more that should be considered.

In this case, without seeing the means, I would expect that the month1 and month2 means differ from baseline by approximately the same amount. A hockey-stick graph of some sort.

SteveDenham

Re: Trend of a continuous variable in a repeated model

tka726 — Fri, 13 Aug 2021 14:16:00 GMT

Thank you so much, this is perfect! And you are absolutely right - the graph looks like a boomerang.