I L L I N O I S UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN

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1 SAS for HLM Edps/Psych/Stat/ 587 Carolyn J. Anderson Department of Educational Psychology I L L I N O I S UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN SAS for HLM Slide 1 of 16

2 Outline SAS & (for Random Intercept Models)... The following will be discussed and demonstrated in class. Outline: Data steps. How to simulate data. SAS for HLM Slide 2 of 16

3 Creating a SAS data set Always Check Log File!! Level 2 Data Log File Merging Two Files Centering Variables Creating a SAS data set. Merging files of different lengths (level 1 & level 2). Creating centered variables. Other SAS for HLM Slide 3 of 16

4 Creating a SAS data set Creating a SAS data set Always Check Log File!! Level 2 Data Log File Merging Two Files Centering Variables * HSB dat1 : level 1 responses; LIBNAME sasdata C:\My Documents\teaching\hlm\lectures\randomintercept ; DATA sasdata.hsb1; INPUT id minority female ses mathach; LABEL id= school minority= Student ethnicity (1=minority, 0=not) female = student gender (1=female, 0=male) ses= standardized scale of student ses mathach= Mathematics achievement ; DATALINES;; Alternatively: LIBNAME mydata C:\My Documents \ teaching\hlm\ lectures \ randomintercept\rawdata.txt ; DATA sasdata.hsb1; infile mydata; INPUT id minority female ses mathach; SAS for HLM Slide 4 of 16

5 Always Check Log File!! Creating a SAS data set Always Check Log File!! Level 2 Data Log File Merging Two Files Centering Variables NOTE: The data set SASDATA.HSB1 has 7185 observations and 5 variables. NOTE: DATA statement used: real time 0.09 seconds cpu time 0.09 seconds SAS for HLM Slide 5 of 16

6 Level 2 Data * hsb2.dat level 2 (schools); Creating a SAS data set Always Check Log File!! Level 2 Data Log File Merging Two Files Centering Variables Need LIBNAME? DATA sasdata.hsb2; INPUT id size sector pracad disclim himinty meanses; LABEL id= school id size= school enrollment sector= 1=Catholic, 0=public pracad= proportion students in academic track disclim= Disciplinary climate himinty= 1=40% minority, 0= <40% minority meanses= Mean SES ; DATALINES; SAS for HLM Slide 6 of 16

7 Log File Creating a SAS data set Always Check Log File!! Level 2 Data Log File Merging Two Files Centering Variables NOTE: The data set SASDATA.HSB2 has 160 observations and 7 variables. NOTE: DATA statement used: real time 0.03 seconds cpu time 0.03 seconds SAS for HLM Slide 7 of 16

8 Merging Two Files Step 1: Sort the data according to variable used to match observations: Creating a SAS data set Always Check Log File!! Level 2 Data Log File Merging Two Files Centering Variables * Combine hsb1 and hsb2 into a single file; * Make sure data files are correctly sorted; PROC SORT DATA=hsb1; by id; PROC SORT DATA=hsb2; by id; Step 2: Merge the two files using the by command Merge the level 1 and level 2 files: DATA hsball; MERGE hsb1 hsb2; BY id; run; Step 3: Check log and Data! (explorer window) SAS for HLM Slide 8 of 16

9 Centering Variables First find the means: Creating a SAS data set Always Check Log File!! Level 2 Data Log File Merging Two Files Centering Variables PROC MEANS data=hsball; by id; var ses; output out=meanses mean=meanses; Merge file with means and main data file and create new variables data hsbcent; merge hsball meanses by id; cses = SES - meanses; RUN; SAS for HLM Slide 9 of 16

10 Basic Syntax: Options CLASS and Model Statements Example of Null HLM 1. options 2. CLASS statement 3. MODEL statement 4. RANDOM statement. 5. TITLE statement. SAS for HLM Slide 10 of 16

11 Options <options go here> ; <various comands on the following lines> Options CLASS and Model Statements Example of Null HLM Options: DATA=<name of sas data set>: what SAS data set to use. NOCLPRINT: don t print classification levels/information. COVTEST: hypothesis tests for variances (& covariances). METHOD: estimation method to use. ML = maximum likelihood REML = restricted maximum likelihood (REML is the default) o SAS for HLM Slide 11 of 16

12 CLASS and Model Statements Options CLASS and Model Statements Example of Null HLM CLASS statement indicates variables that are discrete (nominal), i.e., classification variables. MODEL statement: Name of the response or outcome variable is given to the left of the = sign. Fixed effects are listed on the right side of = sign. MODEL option SOLUTION indicates that you want parameter estimates for the fixed effect output. SAS for HLM Slide 12 of 16

13 Example of Null HLM o Options CLASS and Model Statements Example of Null HLM DATA=sasdata.hsball NOCLPRINT COVTEST METHOD=ML; TITLE HSB: null/empty random intercept model ; CLASS id ; MODEL mathach = / SOLUTION ; RANDOM intercept / SUBJECT = id ; run; SAS for HLM Slide 13 of 16

14 Outline: SAS/ASSIST interactive creating and editing graphs. Saving log file to use commends in SAS program and futher refinements. Exporting graphs to files. SAS for HLM Slide 14 of 16

15 Can be very useful for detecting problems between data and model and assessing whether you have correct code for model. Place code here or walk through SAS program that s on the web SAS for HLM Slide 15 of 16

16 SAS in general: Local (some written by former student): Statistics department has training classes (these cost money) Company: > Support training > Technical support Insight, graphics and MIXED: Course web-site SAS for HLM Slide 16 of 16