Research Question 
: 
How are the different measures of research output distributed? What is the average productivity of Indian scientists? 
Methodology 
: 
Descriptive Statistics using TABLES programme 
Dataset 
: 
ICSOPRU 
$RUN TABLES $FILES PRINT = G_TAB.LST DICTIN = R2R3CM.DIC DATAIN =R3CM.DAT $SETUP INCLUDE V1=360 EXAMPLE OF TABLES PROGRAM PRINT=DICT TABLES TITLE='Univariate statistics for quantitative variables'  ROWVARS=(V363, V365,V367,V369,V371)  USTATS=(MEANSD,MEDMOD) PRINT=NOTABLES
The data matrix is 5 variables and 962 cases 



IDAMS reports analysis specifications: 


Third column Wtsum shows the number of valid cases used for computing univariate statistics of different variables. Standard deviation is greater than the mean value for which indicates large dispersion in the data Skewness is positive for all the variables, indicating a long tail on the right of the mean. Peakedness of the distribution is high: highest for Internal Original Reports. The frequency distribution is highly Leptokurtic. 
Research Question 
: 
What is the extent of inequality in the research output of scientists in India? (Note: Research output is measured by two variables: V363: # of Articles published in the Indian journals; V365: # of Articles published in foreign journals). 
Methodology 
: 
Gini Coefficient 
Dataset 
: 
ICSOPRU 
$RUN QUANTILE $FILES PRINT = G_QUANT.LST DICTIN = R2R3CM.DIC DATAIN = R3CM.DAT $SETUP INCLUDE V1=360 EXAMPLE OF QUANTILE PROGRAM BADDATA=MD1  PRINT=DICT QUANTILE VAR=V363 N=25 PRINT=(FLOR,CLOR) VAR=V365 N=25 PRINT=(FLOR,CLOR)
After filtering 962 cases read from the input data file 


Distribution and Lorenz function for no. of subintervals = 25 Variable no. = 363 S2A:# CM ARTICLES NATL


Lorenz plot variable no. = 363 S2A:# CM ARTICLES NATL 

Fraction of ordered sample 

Gini coefficient = .739 
IDAMS reports that 962 cases were read out of which 831 cases were taken for further analysis the remaining cases were deleted due to missing data. 


Cumulative distribution of articles in 25 classes. 

Lorenz Curve: The area between the equidistribution line and the Lorenz curve indicates the inequality in the output of articles published in Indian journals. 

The value of Gini coefficient = 0.495. It may be noted that the maximum value of Gini coefficient is 1.000. 

Similar analysis was performed for articles published abroad. However the computer output is not shown. The value of Gini coefficient for articles published in foreign journals is 0.739. This value is much higher than that for articles published in Indian journals. These results imply that there is greater inequality in the distribution of articles published abroad, compared with that of articles published in the country. 
Research Question 
: 
What are the factors that inhibit the dissemination of research results? Here is a list of seven factors:
Rank these factors in order of importance based on the collective opinion of respondents. 
Methodology 
: 
Ranking of alternatives 
Dataset 
: 
ICSOPRU 
$RUN RANK $FILES PRINT = RANK.LST DICTIN = R4CM.DIC DATAIN = R4CM.DAT $SETUP INCLUDE V1=496 FACTORS INHIBITIG DISSEMINATION OF RESEARCH RESULTS BADDATA=MD1  METHOD=(CLASSICAL,NONDOMINATED,RANKS)  NALT=7  VARS=(V351V353)  NORMALIZE=YES  PRINT=CDICT PCON=60 DDIS=1 PDIS=5 PCON=50 DDIS=1 PDIS=10 PCON=40 DDIS=1 PDIS=15
***W* RNK003  No valid answer in case no 760 ***W* RNK003  No valid answer in case no 778 ***W* RNK001  Illegal code: 0 in case no 784 ................................................ ................................................ ................................................ After filtering 980 cases read from the input data file 


Methods of fuzzy ranking ************************ Input relation matrix: .0000 .4038 .5204 .5000 .5160 .5510 .5437 The input relation is 

Fuzzy method1 N o n  d o m i n a t e d l a y e r s ******************************************** Membership function of nondominated subset:
Credible alternatives (code or variable no): ******************************************** Membership function of nondominated subset:
Credible alternatives (code or variable no): ******************************************** Membership function of nondominated subset:
Credible alternatives (code or variable no): ******************************************** Membership function of nondominated subset:
Credible alternatives (code or variable no): ******************************************** Membership function of nondominated subset:
Credible alternatives (code or variable no): 5 ******************************************** Membership function of nondominated subset:
Credible alternatives (code or variable no): 7 Final coherence: .3892 intensity: .5896 final dominance: .2295 

Normalized matrix


Fuzzy sets of ranks by alternatives ******************************************
2 Alternative (code or variable no) 3
1 Alternative (code or variable no) 1
4 Alternative (code or variable no) 4
5 Alternative (code or variable no) 2
3 Alternative (code or variable no) 5
6 Alternative (code or variable no) 7
7 

1Fuzzy subsets of alternatives by ranks ************************************** Rank= 1
Credible alternatives (code or variable no): 3 Rank= 2
Credible alternatives (code or variable no): 6 Rank= 3
Credible alternatives (code or variable no): 2 Rank= 4
Credible alternatives (code or variable no): 1 Rank= 5
0Credible alternatives (code or variable no): 4 Rank= 6
Credible alternatives (code or variable no): 5 Rank= 7
Credible alternatives (code or variable no): 7 1 

Method of classical logic ranking Analysis specifications: Rank difference for concordance: 1 

Rerun with new parameters Method of classical logic ranking Analysis specifications: Rank difference for concordance: 1 **************** **************** Method of classical logic ranking Analysis specifications: Rank difference for concordance: 1 **************** **************** 
IDAMS lists the cases containing illegal code or no valid answers. 294 such cases are identified. Out of 980 cases, 686 cases (980294) are processed for analysis. 


Input relational matrix. This is a matrix of fuzzy relations among the set of alternatives. The cells of this matrix indicate the dominance of one alternative over another. For example, the cell (Column 1, Row 2) indicates that the dominance of Alternative 1 over Alternative 2 is 0.4052, whereas the dominance of Alternative 2 over Alternative 1 is 0.4038. In this matrix the values of only seven cells exceed the threshold of simple majority, which means that only a few preferences are expressed in a very clear manner. This is confirmed by the index of cohesion, 0.3892, which seems to be low. However, this index is not poor, when we take into account the small number of alternatives cited (3 out of 7). Intensity = 0.5896. This index can be interpreted as the average credibility of the proposition "Alternative I is preferred to Alternative J" or "Alternative J is preferred to Alternative I" Absolute dominance = 0.2295. This index indicates the average difference between the credibilities of the proposition "Alternative I is preferred to Alternative j" and of the opposite proposition "Alternative J is preferred to Alternative I". 

Fuzzy Method – 1 (Nondominated layers) The cases are presented sequentially from the highest rank and for each of them, the following information is given:
3 > 6 > 1 > 2 > 4 > 7 

Normalized Relational Matrix It can be easily seen that the sum of the cell (1, 2) and cell (2, 1) 0.5009 + 0.4991 = 1.00 Cell( 1, 2) Cell (2, 1) 

Fuzzy sets of Alternatives by rank: All alternatives are listed sequentially with the following information:
Degree of credibility of places of Alternative: We get the following results:
3 > 6 > 2 > 1 > 4 > 5 > 7 

Fuzzy subsets of ranks by alternatives
Rank 1: Alternative with the highest membership value
(.50090) is: 3 We get the following results:
Thus the rank order is: 3 > 6 > 2 > 1 > 4 > 5 > 7 

Method of Classical Ranking (Electre) Parameters Threshold for concordance: 1 Threshold for discordance: 1 Limiting proportion for concordance: 60% Limiting proportion for discordance: 5% All the alternative are nondominating No preference order 

Method of Classical Logic (Electre) Rerun with new parameters: Threshold for concordance: 1 Threshold for discordance: 1 Limiting proportion for concordance: 50% Limiting proportion for discordance: 10% The following rank order is computed: 6, 3 , 1, 4, 2 >5, 7 