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Dataplot Vol 1 Vol 2

STATISTIC MISSING VALUE

Name:
    SET STATISTIC MISSING VALUE (SET)
Type:
    Set Subcommand
Purpose:
    Specify a numeric value that will interpreted as a missing value when computing one of the built-in statistics.
Description:
    Data will often contain missing values. In computing built-in statistics with the LET sub-commands, you can define a value that will be interpreted as a missing value. Data that are equal to this missing value will be omitted from the computation of the statistic.

    In computing a simple statistic LET sub-command such as

      LET A = MEAN Y

    it is relatively easy to omit missing values with a SUBSET clause. For example

      LET A = MEAN Y SUBSET Y <> -99999

    You can also do this with the commands

      SET STATISTIC MISSING VALUE -99999 LET A = MEAN Y SUBSET Y

    Although in this simple case there is no need to use the SET STATISTIC MISSING VALUE, there are 20+ commands (such as CROSS TABULATE, STATISTIC PLOT) that utilize the built-in statistics. In these cases, using the SET STATISTIC MISSING VALUE can be more convenient than using the SUBSET clause.

    Enter HELP STATISTICS for a list of built-in statistics and the commands that can utilize them.

Syntax:
    SET STATISTIC MISSING VALUE <value>
    where <value> is a number or parameter that specifies a value that will be interpreted as a missing value code.
Examples:
    SET STATISTIC MISSING VALUE -9999
    SET STATISTIC MISSING VALUE -1
Note: Default:
    The missing value is set to minimum real value on the machine (this can be determined with a PROBE CPUMIN command).
Synonyms:
    None
Related Commands: Applications:
    Terminal usage
Implementation Date:
    2007/04
Program 1:
     
    read matrix m
    2 4 7 -9999
    2 -9999 2 3
    1 2 -9999 3
    end of data
    .
    set statistic missing value -9999
    .
    let meanv = matrix row mean m
    .
    set write decimals 3
    print meanv
        
    The following output is generated.
    ---------------
              MEANV
    ---------------
              4.333
              2.333
              2.000
        
Program 2:
     
    let n1 = 105
    let n2 = 192
    let n3 = 145
    let n = n1 + n2 + n3
    let x = 3 for i = 1 1 n
    let x = 1 for i = 1 1 n1
    let istrt = n1 + 1
    let istop = n1 + n2
    let x = 2 for i = istrt 1 istop
    .
    set statistic missing value -99
    .
    .  Group 1 values
    .
    let y1 = 0 for i = 1 1 n
    let y2 = 0 for i = 1 1 n
    let y1 = 1 for i = 1 1  81
    let y2 = 1 for i = 1 1  34
    .
    .  Group 2 values (have unequal samples here, so fill
    .          with missing values
    .
    let istrt = n1 + 1
    let istop1 = istrt + 118 - 1
    let istop2 = istrt + 69 - 1
    let y1 = 1 for i = istrt 1 istop1
    let y2 = 1 for i = istrt 1 istop2
    let istrt2 = n1 + 174 + 1
    let istop2 = n1 + n2
    let y2 = -99 for i = istrt2 1 istop2
    .
    .  Group 3 values
    .
    let istrt = n1 + n2 + 1
    let istop1 = istrt + 82 - 1
    let istop2 = istrt + 52 - 1
    let y1 = 1 for i = istrt 1 istop1
    let y2 = 1 for i = istrt 1 istop2
    .
    odds ratio chi-square test y1 y2 x
        
    The following output is generated.
                Summary of Log(Odds Ratio)
     
    ---------------------------------------------------------------------------------------------
                    |                         Log of       Standard
                    |      Odds Ratio     Odds Ratio          Error  1/SE(L(i))**2          w(i)*
              Group |            O(i)           L(i)       SE(L(i))           w(i)        L(i)**2
    ---------------------------------------------------------------------------------------------
                  1 |    6.894114       1.930668      0.3099319       10.41040       38.80455
                  2 |    2.414514      0.8814980      0.2138429       21.86806       16.99233
                  3 |    2.313836      0.8389067      0.2400251       17.35748       12.21558
    ---------------------------------------------------------------------------------------------
              Total |                                                 49.63594       68.01245
     
     
                Chi-Square Analysis of Log(Odds Ratio)
     
    Number of Groups:                           3
    Estimate of Combined Log(Odds Ratio):         1.086652
    Standard Error of Combined Log(Odds Ratio):  0.1419390
     
    Chi-Square Test Statistic (Total):            68.01245
    Degrees of Freeedom:                        3
    CDF of Test Statistic:                        1.000000
     
    Chi-Square Test Statistic (Association):      58.61072
    Degrees of Freedom:                         1
    CDF of Test Statistic:                        1.000000
     
    Chi-Square Test Statistic (Homogeneity):      9.401734
    Degrees of Freedom:                         2
    CDF of Test Statistic:                       0.9978321
     
     
     
                Chi-Square Test for Consistency of Association (Homogeneity)
     
    ---------------------------------------------------------------------------
                                                 Null Hypothesis           Null
               Null     Confidence       Critical     Acceptance     Hypothesis
         Hypothesis          Level          Value       Interval     Conclusion
    ---------------------------------------------------------------------------
         Consistent          50.0%           1.39      (0,0.500)         REJECT
         Consistent          80.0%           3.22      (0,0.800)         REJECT
         Consistent          90.0%           4.61      (0,0.900)         REJECT
         Consistent          95.0%           5.99      (0,0.950)         REJECT
         Consistent          97.5%           7.38      (0,0.975)         REJECT
         Consistent          99.0%           9.21      (0,0.990)         REJECT
     
     
                Chi-Square Test for Overall Degree of Association
     
    ---------------------------------------------------------------------------
                                                 Null Hypothesis           Null
               Null     Confidence       Critical     Acceptance     Hypothesis
         Hypothesis          Level          Value       Interval     Conclusion
    ---------------------------------------------------------------------------
     No Association          50.0%           0.45      (0,0.500)         REJECT
     No Association          80.0%           1.64      (0,0.800)         REJECT
     No Association          90.0%           2.71      (0,0.900)         REJECT
     No Association          95.0%           3.84      (0,0.950)         REJECT
     No Association          97.5%           5.02      (0,0.975)         REJECT
     No Association          99.0%           6.63      (0,0.990)         REJECT
     
     
                Large Sample Confidence Interval for Log(Odds Ratio)
     
    ---------------------------------------------------------------------------------------------------------
                          Log(Odds Ratio)                  Odds Ratio
                         (   1.086652    )             (   2.964332    )
         Confidence          Lower          Upper          Lower          Upper
          Value (%)          Limit          Limit          Limit          Limit
    ---------------------------------------------------------------------------------------------------------
              50.00  0.9909154       1.182388       2.693699       3.262156
              80.00  0.9047496       1.268554       2.471313       3.555707
              90.00  0.8531829       1.320121       2.347105       3.743874
              95.00  0.8084564       1.364847       2.244441       3.915125
              97.50  0.7685093       1.404794       2.156549       4.074689
              99.00  0.7210411       1.452263       2.056573       4.272771
        

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Date created: 06/04/2016
Last updated: 06/04/2016

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