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<<Back Analysis Using SPSS Main Procedure is: Start® All Programs ® SPSS for Windows® SPSS 15.0/ SPSS13.0/ SPSS10.0 (based on the version available on your machine) ® Enter data in Data Editor ® Analyze ® GLM ® Univariate ® calories ® [puts Calories under Dependent list: ] ® blk® [put blk under Fixed Factor(s): ] trt ® [put trt under Fixed Factor(s):] Continue ® Model... [Opens Model dialogue box] ® Custom ® Build Term(s) ® Main effects ® [puts blk, trt under Model: ] ® Continue ® OK.
For performing analysis, input the data in the following format. Here we call the block as BLK and treatment as TRT.
Following are the brief description of the steps along with screen shots. · Open Data editor: Start® All Programs® SPSS for Windows® SPSS 15.0/ SPSS13.0/ SPSS10.0. · Enter
data in SPSS Data editor. There are two views in SPSS Data
Editor. In variable view, one can define the name of
variables and variable types string or numeric and data view
gives the spreadsheet in which data pertaining to variables
may be entered in respective columns. In the present case,
we enter data in numeric format.
·Once the data entry is complete, Choose Analyze from the Menu Bar. Now select Analyze → General linear Model → Univariate.
· This selection displays the following screen
· Select
calories and send it to the Dependent Variable box; blk and
trt may be selected for Fixed
syntax editor.
To test whether there is any significant difference between the average effect of 1st two treatments and the average effect of the remaining 5
treatments. We have to write the treatment contrast in the
syntax editor as follows.
To
compare the treatment 3,4,5,6,7 among themselves we have to
write the treatment contrast in the syntax editor as
follows.
The following window will come.
Click Run → All
To answer the questions from 1 to 5 one can use the following syntax after creating the data file.
UNIANOVA calories BY blk trt /METHOD = SSTYPE(3) /INTERCEPT = INCLUDE /CRITERIA = ALPHA(.05) /Lmatrix 'treatment 1,2 vs treatment 3,4,5,6,7' trt -5 -5 2 2 2 2 2; /Lmatrix 'within treatment 3,4,5,6,7' trt 0 0 1 -1 0 0 0; trt 0 0 1 1 -2 0 0; trt 0 0 1 1 1 -3 0; trt 0 0 1 1 1 1 -4; /Lmatrix '1 vs 2' trt 1 -1 0 0 0 0 0; /Lmatrix '1 vs 3' trt 1 0 -1 0 0 0 0; /Lmatrix '1 vs 4' trt 1 0 0 -1 0 0 0; /Lmatrix '1 vs 5' trt 1 0 0 0 -1 0 0; /Lmatrix '1 vs 6' trt 1 0 0 0 0 -1 0; /Lmatrix '1 vs 7' trt 1 0 0 0 0 0 -1; /Lmatrix '2 vs 3' trt 0 1 -1 0 0 0 0; /Lmatrix '2 vs 4' trt 0 1 0 -1 0 0 0; /Lmatrix '2 vs 5' trt 0 1 0 0 -1 0 0; /Lmatrix '2 vs 6' trt 0 1 0 0 0 -1 0; /Lmatrix '2 vs 7' trt 0 1 0 0 0 0 -1; /Lmatrix '3 vs 4' trt 0 0 1 -1 0 0 0; /Lmatrix '3 vs 5' trt 0 0 1 0 -1 0 0; /Lmatrix '3 vs 6' trt 0 0 1 0 0 -1 0; /Lmatrix '3 vs 7' trt 0 0 1 0 0 0 -1; /Lmatrix '4 vs 5' trt 0 0 0 1 -1 0 0; /Lmatrix '4 vs 6' trt 0 0 0 1 0 -1 0; /Lmatrix '4 vs 7' trt 0 0 0 1 0 0 -1; /Lmatrix '5 vs 6' trt 0 0 0 0 1 -1 0; /Lmatrix '5 vs 7' trt 0 0 0 0 1 0 -1; /Lmatrix '6 vs 7' trt 0 0 0 0 0 1 -1; /DESIGN = trt blk .
Alternatively, all possible pair wise treatment comparisons can be performed using the Button Options on the dialogue box. A click on Button Options, gives the option for estimated marginal means and display means for. From the left hand box, take the effect treatment in the Display means for. Then check the box Compare main effects and then there are 3 options for confidence interval adjustment viz. LSD(none), Bonferrnoni and Sidak. Any one of these 3 options can be selected. Default option is LSD(None). A screen shot for these options is
Alternatively to answer the questions from 1 to 5 one can use the following syntax after creating the data file.
UNIANOVA calories BY blk trt /METHOD = SSTYPE(3) /INTERCEPT = INCLUDE /EMMEANS = TABLES(trt) COMPARE ADJ(LSD) /CRITERIA = ALPHA(.05) /Lmatrix 'treatment 1,2 vs treatment 3,4,5,6,7' trt -5 -5 2 2 2 2 2; /Lmatrix 'within treatment 3,4,5,6,7' trt 0 0 1 -1 0 0 0; trt 0 0 1 1 -2 0 0; trt 0 0 1 1 1 -3 0; trt 0 0 1 1 1 1 -4;
/DESIGN = trt blk .
Analysis Using SAS Analysis Using SPSS
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Descriptive Statistics | |||||
Tests of Significance | |||||
Correlation and Regression | |||||
Completely Randomised Design | |||||
RCB Design | |||||
Incomplete Block Design | |||||
Resolvable Block Design | |||||
Augmented Design | |||||
Factorial RCB Design | |||||
Partially Confounded Design | |||||
Factorial Experiment with Extra Treatments | |||||
Split Plot Design | |||||
Strip Plot Design | |||||
Response Surface Design | |||||
Cross Over Design | |||||
Analysis of Covariance | |||||
Diagnostics and Remedial Measures | |||||
Principal Component Analysis | |||||
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Groups of Experiments | |||||
Non-Linear Models | |||||
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For
exposure on SAS, SPSS, Please see Module I of Electronic Book II: Advances in Data Analytical Techniques available at Design Resource Server(www.iasri.res.in/design) |
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