When it appeared to check on whether the read command was properly executed. William. E. Becker Module One, Part Two: Using LIMDEP Sept. 15, 2008: p. 12
William. E. Becker Module One, Part Two: Using LIMDEP Sept. 15, 2008: p. 13
READING LARGE FILES INTO LIMDEP LIMDEP has a data matrix default restriction of no more than 222 rows (records per variable), 900 columns (number of variables) and 200,000 cells. To read, import or create nonconforming data sets this default setting must be changed. For example, to accommodate larger data sets the number of rows must be increased. If the creation of more than 900 variables is anticipated, even if less than 900 variables were initially imported, then the number of columns must be increased before any data is read. This is accomplished by clicking the project button on the top ribbon, going to settings, and changing the number of cells and number of rows. As an example, consider the data set employed by Becker and Powers (2001), which initially had 2,837 records. Open LIMDEP and go to “Project” and then “Settings…,” which yields the following screen display: William. E. Becker Module One, Part Two: Using LIMDEP Sept. 15, 2008: p. 14
Increasing the “Number of Cells” from 200,000 to 2,000,000 and increasing “Rows” from 222 to 3,000, automatically resets the “Columns” to 666, which is more than sufficient to read the 64 variables in the initial data set and to accommodate any variables to be created within LIMDEP. Pressing “OK” resets the memory allocation that LIMDEP will employ for this data set. William. E. Becker Module One, Part Two: Using LIMDEP Sept. 15, 2008: p. 15
This Becker and Powers data set does not have variable names imbedded in it. Thus, they will be added to the read command. To now read the data follow the path “Files” to “New” to “Text/Command Document” and click “OK.” Entering the following read statement into the Text/Command file, highlighting it, and pushing the green “Go” button will enter the 2,837 records on 64 variables in file beck8WO into LIMDEP and each of the variables will be named as indicated by each two character label. READ; NREC=2837; NVAR=64; FILE=F: \beck8WO.csv; Names= A1,A2,X3, C,AL,AM,AN,CA,CB,CC,CH,CI,CJ,CK,CL,CM,CN,CO,CS,CT, CU,CV,CW,DB,DD,DI,DJ,DK,DL,DM,DN,DQ,DR,DS,DY,DZ,EA,EB,EE,EF, EI,EJ,EP,EQ,ER,ET,EY,EZ,FF,FN,FX,FY,FZ,GE,GH,GM,GN,GQ,GR,HB, HC,HD,HE,HF $ William. E. Becker Module One, Part Two: Using LIMDEP Sept. 15, 2008: p. 16
Defining all the variables is not critical for our purposes here, but the variables used in the Becker and Power’s study required the following definitions (where names are not upper- and lower-case sensitive): A1: Term, where 1= fall, 2 = spring A2: School code, where 100/199 = doctorate, 200/299 = comprehensive, 300/399 = lib arts, 400/499 = 2 year hb: initial class size (number taking preTUCE) hc: final class size (number taking postTUCE) dm: experiences measured by number of years teaching dj: teacher’s highest degree, where Bachelors=1, Masters=2, PhD=3 cc: postTUCE score (0 to 30) an: preTUCE score (0 to 30) ge: Student evaluation measured interest gh: Student evaluation measured textbook quality gm: Student evaluation measured regular instructor’s English ability gq:
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- Regression Analysis, LIMDEP