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Run MATRIX procedure:

*********************** MEMORE Procedure for SPSS Version 3.0 ***********************

                           Written by Amanda Montoya

                    Documentation available at github.com/akmontoya/MEMORE

**************************** ANALYSIS NOTES AND WARNINGS ****************************

Number of samples for Monte Carlo condifidence intervals:
  5000

The following variables were mean centered prior to analysis:
 (        TSRQ_T2   +       TSRQ_T1  )        /2
 (        WEMBS_T2  +       WEMBS_T1 )        /2

Level of confidence for all confidence intervals in output:
      95.00

**************************************************************************************

Model:
  18

Variables:
Y =   DASSS_T2 DASSS_T1
W =   BMI
M1 =  TSRQ_T2  TSRQ_T1
M2 =  WEMBS_T2 WEMBS_T1

Computed Variables:
Ydiff =           DASSS_T2  -       DASSS_T1
M1diff =          TSRQ_T2   -       TSRQ_T1
M2diff =          WEMBS_T2  -       WEMBS_T1
M1avg  = (        TSRQ_T2   +       TSRQ_T1  )        /2                         Centered
M2avg  = (        WEMBS_T2  +       WEMBS_T1 )        /2                         Centered

Sample Size:
  63

**************************************************************************************
Outcome: Ydiff =  DASSS_T2  -       DASSS_T1

Model Summary
          R       R-sq        MSE          F        df1        df2          p
      .1110      .0123    18.4397      .7612     1.0000    61.0000      .3864

Model
               Coef         SE          t          p       LLCI       ULCI
constant    -4.7456     2.0201    -2.3493      .0221    -8.7837     -.7076
W             .0683      .0782      .8724      .3864     -.0881      .2247

Degrees of freedom for all regression coefficient estimates:
  61

Conditional Effect of Focal Predictor on Outcome at values of Moderator(s)
 Focal:   'X'      (X)
 Outcome: Ydiff    (Y)
 Mod:     BMI      (W)


        BMI     Effect         SE          t          p       LLCI       ULCI
    17.9047    -3.5234      .7682    -4.5867      .0000    -5.0595    -1.9873
    24.8748    -3.0476      .5410    -5.6332      .0000    -4.1294    -1.9658
    31.8449    -2.5718      .7682    -3.3479      .0014    -4.1079    -1.0357

     Values for quantitative moderators are the mean and plus/minus one SD from the mean.

Degrees of freedom for all conditional effects:
  61

**************************************************************************************
Outcome: M1diff = TSRQ_T2   -       TSRQ_T1

Model
               Coef         SE          t          p       LLCI       ULCI
constant     1.2381      .8625     1.4355      .1562     -.4860     2.9621

Degrees of freedom for all regression coefficient estimates:
  62

**************************************************************************************
Outcome: M2diff = WEMBS_T2  -       WEMBS_T1

Model
               Coef         SE          t          p       LLCI       ULCI
constant     1.6349      .6252     2.6152      .0112      .3852     2.8846

Degrees of freedom for all regression coefficient estimates:
  62

**************************************************************************************
Outcome: Ydiff =  DASSS_T2  -       DASSS_T1

Model Summary
          R       R-sq        MSE          F        df1        df2          p
      .5152      .2655    14.6758     4.1202     5.0000    57.0000      .0029

Model
               Coef         SE          t          p       LLCI       ULCI
constant    -4.1087     1.9026    -2.1595      .0350    -7.9187     -.2987
W             .0615      .0724      .8494      .3992     -.0834      .2064
M1diff        .0688      .0719      .9573      .3424     -.0751      .2127
M2diff       -.3383      .1028    -3.2894      .0017     -.5442     -.1323
M1avg        -.0033      .0592     -.0557      .9558     -.1219      .1153
M2avg        -.2746      .1269    -2.1637      .0347     -.5287     -.0205

Degrees of freedom for all regression coefficient estimates:
  57

--------------------------------------------------------------------------------------

Conditional Effect of Focal Predictor on Outcome at values of Moderator(s)
 Focal:   'X'      (X)
 Outcome: Ydiff    (Y)
 Mod:     BMI      (W)


        BMI      M1avg      M2avg     Effect         SE          t          p       LLCI       ULCI
    17.9047     1.0269     -.5395    -2.8634      .7440    -3.8486      .0003    -4.3533    -1.3735
    24.8748      .0000      .0000    -2.5797      .5215    -4.9471      .0000    -3.6239    -1.5355
    31.8449    -1.0269      .5395    -2.2961      .6934    -3.3111      .0016    -3.6846     -.9075

     Values for quantitative moderators are the mean and plus/minus one SD from the mean.

     Values for mediator averages are the conditional values based on the values of the moderator.

--------------------------------------------------------------------------------------

Degrees of freedom for all conditional effects:
  57

******************* CONDITIONAL TOTAL, DIRECT, AND INDIRECT EFFECTS *******************

Conditional Total Effect of X on Y at values of the Moderator(s)
        BMI     Effect         SE          t         df          p       LLCI       ULCI
    17.9047    -3.5234      .7682    -4.5867    61.0000      .0000    -5.0595    -1.9873
    24.8748    -3.0476      .5410    -5.6332    61.0000      .0000    -4.1294    -1.9658
    31.8449    -2.5718      .7682    -3.3479    61.0000      .0014    -4.1079    -1.0357

     Values for quantitative moderators are the mean and plus/minus one SD from the mean.

Conditional Direct Effect of X on Y at values of the Moderator(s)
        BMI      M1avg      M2avg     Effect         SE          t         df          p       LLCI       ULCI
    17.9047     1.0269     -.5395    -2.8634      .7440    -3.8486    57.0000      .0003    -4.3533    -1.3735
    24.8748      .0000      .0000    -2.5797      .5215    -4.9471    57.0000      .0000    -3.6239    -1.5355
    31.8449    -1.0269      .5395    -2.2961      .6934    -3.3111    57.0000      .0016    -3.6846     -.9075

     Values for quantitative moderators are the mean and plus/minus one SD from the mean.

     Values for mediator averages (Mavg) are the conditional values based on the values of the moderator.

Indirect Effect of X on Y through M
          Effect       MCSE     MCLLCI     MCULCI
Ind1       .0852      .1259     -.1034      .3984
Ind2      -.5531      .2704    -1.1617     -.0996
Total     -.4679      .3032    -1.1204      .0908

Indirect Key
Ind1  'X'      ->       M1diff   ->       Ydiff
Ind2  'X'      ->       M2diff   ->       Ydiff

******************************** INDICES OF MODERATION ********************************

Test of Moderation of the Total Effect
      Effect         SE          t         df          p       LLCI       ULCI
W      .0683      .0782      .8724    61.0000      .3864     -.0881      .2247

Test of Moderation of the Direct Effect
      Effect         SE          t         df          p       LLCI       ULCI
W      .0615      .0724      .8494    57.0000      .3992     -.0834      .2064

------ END MATRIX -----

