Mplus VERSION 7.4
MUTHEN & MUTHEN
10/17/2015 3:34 PM
INPUT INSTRUCTIONS
title: Hayes PMI multiple mediators example
data:
file = pmi.txt;
variable:
names = cond pmi import reaction gender age;
usev = reaction import pmi cond;
analysis:
estimator = Bayes;
processors = 2;
biter = (20000);
model:
reaction on import pmi cond;
import on cond;
pmi on cond;
import with pmi;
model indirect:
reaction IND cond;
output:
tech1 tech8 cinterval;
plot:
type = plot3;
INPUT READING TERMINATED NORMALLY
Hayes PMI multiple mediators example
SUMMARY OF ANALYSIS
Number of groups 1
Number of observations 123
Number of dependent variables 3
Number of independent variables 1
Number of continuous latent variables 0
Observed dependent variables
Continuous
REACTION IMPORT PMI
Observed independent variables
COND
Estimator BAYES
Specifications for Bayesian Estimation
Point estimate MEDIAN
Number of Markov chain Monte Carlo (MCMC) chains 2
Random seed for the first chain 0
Starting value information UNPERTURBED
Treatment of categorical mediator LATENT
Algorithm used for Markov chain Monte Carlo GIBBS(PX1)
Convergence criterion 0.500D-01
Maximum number of iterations 50000
K-th iteration used for thinning 1
Input data file(s)
pmi.txt
Input data format FREE
THE MODEL ESTIMATION TERMINATED NORMALLY
USE THE FBITERATIONS OPTION TO INCREASE THE NUMBER OF ITERATIONS BY A FACTOR
OF AT LEAST TWO TO CHECK CONVERGENCE AND THAT THE PSR VALUE DOES NOT INCREASE.
MODEL FIT INFORMATION
Number of Free Parameters 12
Bayesian Posterior Predictive Checking using Chi-Square
95% Confidence Interval for the Difference Between
the Observed and the Replicated Chi-Square Values
-13.196 14.524
Posterior Predictive P-Value 0.478
Information Criteria
Deviance (DIC) 1315.474
Estimated Number of Parameters (pD) 11.658
Bayesian (BIC) 1349.661
MODEL RESULTS
Posterior One-Tailed 95% C.I.
Estimate S.D. P-Value Lower 2.5% Upper 2.5% Significance
REACTION ON
IMPORT 0.325 0.072 0.000 0.183 0.467 *
PMI 0.397 0.094 0.000 0.210 0.582 *
COND 0.102 0.242 0.334 -0.376 0.581
IMPORT ON
COND 0.624 0.317 0.023 0.010 1.259 *
PMI ON
COND 0.476 0.243 0.027 -0.006 0.954
IMPORT WITH
PMI 0.597 0.227 0.002 0.190 1.081 *
Intercepts
REACTION -0.157 0.535 0.382 -1.206 0.905
IMPORT 3.907 0.218 0.000 3.480 4.333 *
PMI 5.376 0.166 0.000 5.050 5.702 *
Residual Variances
REACTION 1.703 0.229 0.000 1.333 2.225 *
IMPORT 3.065 0.409 0.000 2.400 3.988 *
PMI 1.773 0.238 0.000 1.383 2.323 *
TOTAL, TOTAL INDIRECT, SPECIFIC INDIRECT, AND DIRECT EFFECTS
Posterior One-Tailed 95% C.I.
Estimate S.D. P-Value Lower 2.5% Upper 2.5% Significance
Effects from COND to REACTION
Total 0.499 0.285 0.042 -0.066 1.055
Total indirect 0.386 0.172 0.007 0.070 0.749 *
Specific indirect
REACTION
IMPORT
COND 0.194 0.115 0.023 0.003 0.458 *
REACTION
PMI
COND 0.180 0.109 0.027 -0.002 0.429
Direct
REACTION
COND 0.102 0.242 0.334 -0.376 0.581
CREDIBILITY INTERVALS OF MODEL RESULTS
Lower .5% Lower 2.5% Lower 5% Estimate Upper 5% Upper 2.5% Upper .5%
REACTION ON
IMPORT 0.140 0.183 0.206 0.325 0.445 0.467 0.510
PMI 0.147 0.210 0.241 0.397 0.552 0.582 0.639
COND -0.518 -0.376 -0.294 0.102 0.501 0.581 0.748
IMPORT ON
COND -0.187 0.010 0.103 0.624 1.151 1.259 1.452
PMI ON
COND -0.153 -0.006 0.078 0.476 0.878 0.954 1.104
IMPORT WITH
PMI 0.066 0.190 0.252 0.597 0.992 1.081 1.274
Intercepts
REACTION -1.528 -1.206 -1.028 -0.157 0.730 0.905 1.247
IMPORT 3.351 3.480 3.550 3.907 4.263 4.333 4.462
PMI 4.952 5.050 5.104 5.376 5.653 5.702 5.802
Residual Variances
REACTION 1.234 1.333 1.385 1.703 2.128 2.225 2.439
IMPORT 2.234 2.400 2.494 3.065 3.817 3.988 4.373
PMI 1.289 1.383 1.437 1.773 2.218 2.323 2.502
CREDIBILITY INTERVALS OF TOTAL, TOTAL INDIRECT, SPECIFIC INDIRECT, AND DIRECT EFFECTS
Lower .5% Lower 2.5% Lower 5% Estimate Upper 5% Upper 2.5% Upper .5%
Effects from COND to REACTION
Total -0.244 -0.066 0.025 0.499 0.967 1.055 1.230
Total indirect -0.023 0.070 0.122 0.386 0.686 0.749 0.880
Specific indirect
REACTION
IMPORT
COND -0.060 0.003 0.031 0.194 0.408 0.458 0.562
REACTION
PMI
COND -0.062 -0.002 0.028 0.180 0.382 0.429 0.520
Direct
REACTION
COND -0.518 -0.376 -0.294 0.102 0.501 0.581 0.748
TECHNICAL 1 OUTPUT
PARAMETER SPECIFICATION
NU
REACTION IMPORT PMI COND
________ ________ ________ ________
1 0 0 0 0
LAMBDA
REACTION IMPORT PMI COND
________ ________ ________ ________
REACTION 0 0 0 0
IMPORT 0 0 0 0
PMI 0 0 0 0
COND 0 0 0 0
THETA
REACTION IMPORT PMI COND
________ ________ ________ ________
REACTION 0
IMPORT 0 0
PMI 0 0 0
COND 0 0 0 0
ALPHA
REACTION IMPORT PMI COND
________ ________ ________ ________
1 1 2 3 0
BETA
REACTION IMPORT PMI COND
________ ________ ________ ________
REACTION 0 4 5 6
IMPORT 0 0 0 7
PMI 0 0 0 8
COND 0 0 0 0
PSI
REACTION IMPORT PMI COND
________ ________ ________ ________
REACTION 9
IMPORT 0 10
PMI 0 11 12
COND 0 0 0 0
STARTING VALUES
NU
REACTION IMPORT PMI COND
________ ________ ________ ________
1 0.000 0.000 0.000 0.000
LAMBDA
REACTION IMPORT PMI COND
________ ________ ________ ________
REACTION 1.000 0.000 0.000 0.000
IMPORT 0.000 1.000 0.000 0.000
PMI 0.000 0.000 1.000 0.000
COND 0.000 0.000 0.000 1.000
THETA
REACTION IMPORT PMI COND
________ ________ ________ ________
REACTION 0.000
IMPORT 0.000 0.000
PMI 0.000 0.000 0.000
COND 0.000 0.000 0.000 0.000
ALPHA
REACTION IMPORT PMI COND
________ ________ ________ ________
1 3.484 4.203 5.602 0.000
BETA
REACTION IMPORT PMI COND
________ ________ ________ ________
REACTION 0.000 0.000 0.000 0.000
IMPORT 0.000 0.000 0.000 0.000
PMI 0.000 0.000 0.000 0.000
COND 0.000 0.000 0.000 0.000
PSI
REACTION IMPORT PMI COND
________ ________ ________ ________
REACTION 1.192
IMPORT 0.000 1.496
PMI 0.000 0.000 0.866
COND 0.000 0.000 0.000 0.125
PRIORS FOR ALL PARAMETERS PRIOR MEAN PRIOR VARIANCE PRIOR STD. DEV.
Parameter 1~N(0.000,infinity) 0.0000 infinity infinity
Parameter 2~N(0.000,infinity) 0.0000 infinity infinity
Parameter 3~N(0.000,infinity) 0.0000 infinity infinity
Parameter 4~N(0.000,infinity) 0.0000 infinity infinity
Parameter 5~N(0.000,infinity) 0.0000 infinity infinity
Parameter 6~N(0.000,infinity) 0.0000 infinity infinity
Parameter 7~N(0.000,infinity) 0.0000 infinity infinity
Parameter 8~N(0.000,infinity) 0.0000 infinity infinity
Parameter 9~IG(-1.000,0.000) infinity infinity infinity
Parameter 10~IW(0.000,-3) infinity infinity infinity
Parameter 11~IW(0.000,-3) infinity infinity infinity
Parameter 12~IW(0.000,-3) infinity infinity infinity
TECHNICAL 8 OUTPUT
Kolmogorov-Smirnov comparing posterior distributions across chains 1 and 2 using 100 draws.
Parameter KS Statistic P-value
Parameter 11 0.1400 0.2606
Parameter 7 0.1300 0.3439
Parameter 1 0.1300 0.3439
Parameter 9 0.1200 0.4431
Parameter 3 0.0900 0.7942
Parameter 10 0.0800 0.8938
Parameter 12 0.0800 0.8938
Parameter 6 0.0700 0.9610
Parameter 4 0.0700 0.9610
Parameter 8 0.0700 0.9610
Parameter 2 0.0600 0.9921
Parameter 5 0.0300 1.0000
Simulated prior distributions
Parameter Prior Mean Prior Variance Prior Std. Dev.
Parameter 1 Improper Prior
Parameter 2 Improper Prior
Parameter 3 Improper Prior
Parameter 4 Improper Prior
Parameter 5 Improper Prior
Parameter 6 Improper Prior
Parameter 7 Improper Prior
Parameter 8 Improper Prior
Parameter 9 Improper Prior
Parameter 10 Improper Prior
Parameter 11 Improper Prior
Parameter 12 Improper Prior
TECHNICAL 8 OUTPUT FOR BAYES ESTIMATION
CHAIN BSEED
1 0
2 285380
POTENTIAL PARAMETER WITH
ITERATION SCALE REDUCTION HIGHEST PSR
100 1.010 8
200 1.014 7
300 1.008 10
400 1.006 4
500 1.009 4
600 1.004 1
700 1.002 1
800 1.000 1
900 1.000 1
1000 1.002 12
1100 1.002 12
1200 1.003 12
1300 1.001 12
1400 1.002 12
1500 1.001 12
1600 1.002 6
1700 1.001 2
1800 1.001 2
1900 1.000 7
2000 1.000 7
2100 1.001 9
2200 1.002 9
2300 1.002 9
2400 1.001 5
2500 1.002 9
2600 1.001 9
2700 1.001 9
2800 1.001 9
2900 1.001 9
3000 1.001 9
3100 1.000 9
3200 1.001 9
3300 1.001 9
3400 1.002 9
3500 1.001 9
3600 1.001 9
3700 1.000 6
3800 1.000 12
3900 1.000 12
4000 1.000 12
4100 1.000 12
4200 1.000 1
4300 1.000 1
4400 1.000 2
4500 1.000 2
4600 1.000 2
4700 1.000 7
4800 1.000 4
4900 1.000 4
5000 1.000 7
5100 1.000 7
5200 1.000 8
5300 1.000 8
5400 1.001 4
5500 1.000 4
5600 1.000 8
5700 1.001 8
5800 1.001 8
5900 1.001 8
6000 1.001 8
6100 1.001 8
6200 1.001 8
6300 1.001 8
6400 1.001 4
6500 1.000 4
6600 1.001 4
6700 1.000 4
6800 1.001 4
6900 1.000 4
7000 1.001 4
7100 1.001 4
7200 1.001 4
7300 1.001 4
7400 1.001 4
7500 1.001 4
7600 1.000 4
7700 1.000 4
7800 1.000 4
7900 1.000 4
8000 1.000 4
8100 1.000 2
8200 1.000 4
8300 1.000 4
8400 1.000 4
8500 1.000 4
8600 1.000 4
8700 1.000 4
8800 1.000 4
8900 1.000 4
9000 1.000 4
9100 1.000 4
9200 1.000 4
9300 1.000 4
9400 1.000 10
9500 1.000 10
9600 1.000 10
9700 1.000 10
9800 1.000 9
9900 1.000 10
10000 1.000 10
10100 1.000 10
10200 1.000 10
10300 1.000 10
10400 1.000 10
10500 1.000 10
10600 1.000 10
10700 1.000 10
10800 1.000 4
10900 1.000 4
11000 1.000 4
11100 1.000 4
11200 1.000 4
11300 1.001 4
11400 1.000 4
11500 1.000 4
11600 1.000 10
11700 1.000 4
11800 1.000 10
11900 1.000 10
12000 1.000 10
12100 1.000 10
12200 1.000 4
12300 1.000 4
12400 1.000 8
12500 1.000 10
12600 1.000 10
12700 1.000 10
12800 1.000 10
12900 1.000 10
13000 1.000 4
13100 1.000 10
13200 1.000 10
13300 1.000 10
13400 1.000 10
13500 1.000 10
13600 1.000 10
13700 1.000 10
13800 1.000 8
13900 1.000 10
14000 1.000 8
14100 1.000 8
14200 1.000 8
14300 1.000 8
14400 1.000 8
14500 1.000 8
14600 1.000 8
14700 1.000 4
14800 1.000 4
14900 1.000 7
15000 1.000 5
15100 1.000 7
15200 1.000 7
15300 1.000 2
15400 1.000 5
15500 1.000 5
15600 1.000 5
15700 1.000 5
15800 1.000 5
15900 1.000 5
16000 1.000 5
16100 1.000 5
16200 1.000 5
16300 1.000 5
16400 1.000 5
16500 1.000 5
16600 1.000 5
16700 1.000 5
16800 1.000 9
16900 1.000 8
17000 1.000 10
17100 1.000 8
17200 1.000 8
17300 1.000 8
17400 1.000 6
17500 1.000 6
17600 1.000 6
17700 1.000 6
17800 1.000 6
17900 1.000 6
18000 1.000 6
18100 1.000 6
18200 1.000 6
18300 1.000 6
18400 1.000 6
18500 1.000 6
18600 1.000 6
18700 1.000 10
18800 1.000 3
18900 1.000 3
19000 1.000 3
19100 1.000 3
19200 1.000 3
19300 1.000 3
19400 1.000 3
19500 1.000 3
19600 1.000 3
19700 1.000 3
19800 1.000 3
19900 1.000 3
20000 1.000 3
PLOT INFORMATION
The following plots are available:
Histograms (sample values)
Scatterplots (sample values)
Bayesian posterior parameter distributions
Bayesian posterior parameter trace plots
Bayesian autocorrelation plots
Bayesian posterior predictive checking scatterplots
Bayesian posterior predictive checking distribution plots
DIAGRAM INFORMATION
Use View Diagram under the Diagram menu in the Mplus Editor to view the diagram.
If running Mplus from the Mplus Diagrammer, the diagram opens automatically.
Diagram output
c:\users\bengt 2013\documents\bengt\mplus runs\a book - topic 1 mplus runs\path analysis\hayes p
Beginning Time: 15:34:06
Ending Time: 15:34:06
Elapsed Time: 00:00:00
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