
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:
  15

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    -8.7850     -.7062
W             .0683      .0782      .8724      .3864     -.0882      .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 Summary
          R       R-sq        MSE          F        df1        df2          p
      .1026      .0105    47.1285      .6491     1.0000    61.0000      .4236

Model
               Coef         SE          t          p       LLCI       ULCI
constant     3.7449     3.2294     1.1596      .2507    -2.7128    10.2027
W            -.1008      .1251     -.8057      .4236     -.3509      .1493

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: M1diff   (M)
 Mod:     BMI      (W)


        BMI     Effect         SE          t          p       LLCI       ULCI
    17.9047     1.9405     1.2281     1.5801      .1193     -.5152     4.3963
    24.8748     1.2381      .8649     1.4315      .1574     -.4914     2.9676
    31.8449      .5357     1.2281      .4362      .6643    -1.9201     2.9914

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

Degrees of freedom for all conditional effects:
  61

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

Model Summary
          R       R-sq        MSE          F        df1        df2          p
      .1432      .0205    24.5128     1.2779     1.0000    61.0000      .2627

Model
               Coef         SE          t          p       LLCI       ULCI
constant     4.1716     2.3291     1.7911      .0782     -.4857     8.8289
W            -.1020      .0902    -1.1304      .2627     -.2824      .0784

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: M2diff   (M)
 Mod:     BMI      (W)


        BMI     Effect         SE          t          p       LLCI       ULCI
    17.9047     2.3457      .8857     2.6484      .0103      .5746     4.1168
    24.8748     1.6349      .6238     2.6210      .0111      .3876     2.8822
    31.8449      .9241      .8857     1.0434      .3009     -.8469     2.6952

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

Degrees of freedom for all conditional effects:
  61

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

Model Summary
          R       R-sq        MSE          F        df1        df2          p
      .5061      .2562    14.6053     4.9939     4.0000    58.0000      .0016

Model
               Coef         SE          t          p       LLCI       ULCI
constant    -2.5543      .5193    -4.9182      .0000    -3.5939    -1.5147
M1diff        .0615      .0712      .8646      .3908     -.0809      .2040
M2diff       -.3484      .1019    -3.4184      .0012     -.5524     -.1444
M1avg        -.0104      .0585     -.1784      .8590     -.1276      .1067
M2avg        -.2557      .1246    -2.0512      .0448     -.5051     -.0062

Degrees of freedom for all regression coefficient estimates:
  58

******************* 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.

Direct effect of X on Y
     Effect         SE          t         df          p       LLCI       ULCI
    -2.5543      .5193    -4.9182    58.0000      .0000    -3.5939    -1.5147

Conditional Indirect Effect of X on Y through Mediator at values of the Moderator
  Ind:      Ind1
  Med:      M1diff    (M1)


        BMI     Effect       MCSE     MCLLCI     MCULCI
    17.9047      .1194      .3983     -.5933     1.0996
    24.8748      .0762      .4313     -.7682     1.1021
    31.8449      .0330      .4805     -.9540     1.1373

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

Conditional Indirect Effect of X on Y through Mediator at values of the Moderator
  Ind:      Ind2
  Med:      M2diff    (M2)


        BMI     Effect       MCSE     MCLLCI     MCULCI
    17.9047     -.8172     1.0767    -3.1947     1.1593
    24.8748     -.5695     1.2079    -3.2097     1.7658
    31.8449     -.3219     1.3686    -3.2914     2.3323

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

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     -.0882      .2247

Index of Moderated Mediation for each Indirect Effect.
          Effect       MCSE     MCLLCI     MCULCI
Ind1      -.0062      .0134     -.0386      .0169
Ind2       .0355      .0343     -.0264      .1106

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

