Split Plot Design with Repeated Measures

snca229 — Tue, 20 Aug 2019 20:25:52 GMT

Hello SAS Community!

I am having a bit of trouble figuring out the best code to use for my experiment. The more I work to fix my syntax, the more confused that I get.

Background: This is set up as a split plot design with repeated measures. The main plot is two different animal diets (n=5 per treatment). The subplot consists of each animal being treated with 7 different hormones and having one control. Response variable were measured at 4 different time periods (24, 48, 72, and 96 hours). The data is non-normally distributed and a log transformation must be done. Homogeneity is good. Below is my code with example data (not complete or accurate responses).

I also need to correctly get a means separation test into the code.

Note: red and green refer to the two different diets.

data CLP4;

input diet $ hormone $ P24 P48 P72 P96;

logP24=log(P24);

logP48=log(P48);

logP72=log(P72);

logP96=log(P96);

datalines;

Green Control 861.32 162.11 119.865 28.276

Green Control 1135.02 238.79 155.245 29.156

Red Control 735.28 236.76 162.445 55.276

Red Control 605.66 159.37 85.745 23.012

Red hCGhigh 1327.96 313.22 110.92 23.348

Red hCGhigh 1270.6 338.74 179.25 65.848

Green hCGhigh 511.02 179.81 132.59 65.81

Green hCGhigh 583.68 186.54 147.97 65.214

Red hCGlow 1593.04 178.93 129.305 24.524

Red hCGlow 1217.32 188.14 116.29 34.58

Green hCGlow 1124.98 215.46 172.355 53.776

Green hCGlow 1134.72 307.38 182.755 53.194

Green Lhhigh 1066.66 174.89 98.87 21.806

Green Lhhigh 971.68 157.94 96.47 29.132

Red Lhhigh 1269.44 203.6 129.8 28.152

Red Lhhigh 1116.28 205.19 117.04 36.484

Green Lhlow 1579.42 157.65 87.445 16.3618

Green Lhlow 832.18 141.38 . 21.344

Red Lhlow 1164.04 236.01 117.305 43.928

Red Lhlow 1229.82 245.31 120.22 21.252

Green Lhlow 880.78 166.95 166.25 53.41

Green Lhlow 824.12 192.95 208.71 75.614

Green PGEhigh 892 168.11 127.925 44.886

Green PGEhigh 909.5 240.74 133.37 28.458

Red PGEhigh 1025.72 311.68 206.7 56.778

Red PGEhigh 1163.88 313.18 174.51 44.816

Green PGElow 1170.58 232.94 160.64 39.612

Green PGElow 1167.52 277.79 150.705 38.01

Red PGElow 658.18 198.81 118.925 30.568

Red PGElow 776.2 221.04 145.615 46.994

Red PGEmed 1095.34 277.01 229.63 70.582

Red PGEmed 896.92 309.11 175.595 64.732

Green PGEmed 1051.36 288.48 212.295 63.306

Green PGEmed 1368.44 267.82 244.565 93.674

;

proc mixed data CLP4;

class diet hormone;

model logP24- -logP96= diet hormone diet*hormone/ ddfm=KR;

repeated time 4 (24 48 72 96) polynomial/summary printe;

lsmeans diet hormone diet*hormone/pdiff lines;

run;

Re: Split Plot Design with Repeated Measures

RyanKCarr — Thu, 22 Aug 2019 19:31:17 GMT

Hi,

I'm not quite sure from your question what your goal is. If you are looking for a multivariate response, would something like the following help?

I've also included time as a numeric variable in case you were looking to leverage the linear (or non-linear) structure of change over time, but I haven't worked that into the model yet.

Ryan

data clp4y ;
   set clp4 ;
   logy = logp24 ;
   var = 'logp24' ;
   time = 24 ;
   output ;
   logy = logp48 ;
   var = 'logp48' ;
   time = 48 ;
   output ;
   logy = logp72 ;
   var = 'logp72' ;
   time = 72 ;
   output ;
   logy = logp96 ;
   var = 'logp96' ;
   time = 96 ;
   output ;

run ;

proc mixed data=CLP4y ;
      class var diet hormone;
      model logy = var diet hormone diet*hormone/ ddfm=KR;
      repeated var / r ;
      lsmeans diet hormone diet*hormone / pdiff=all ;
      *repeated time 4 (24 48 72 96) polynomial/summary printe;
      *lsmeans diet hormone diet*hormone/pdiff lines;
run;

topic Split Plot Design with Repeated Measures in SAS Programming

Split Plot Design with Repeated Measures

Re: Split Plot Design with Repeated Measures