“Mplus ANALYSIS”的版本间的差异

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ANALYSIS
+
ANALYSIS命令语法
 +
{| <tbody>
 +
| width="168" | ANALYSIS:
 +
| width="294" |
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" |
 +
| width="120" |
 +
|-
 +
| width="168" | TYPE =
 +
| width="294" | <strong>GEN</strong>ERAL;
 +
| width="120" | GENERAL
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>    BAS</strong>IC;
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>    RAND</strong>OM;
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>    COM</strong>PLEX;
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>MIX</strong>TURE;
 +
<strong>    BAS</strong>IC;
 +
<strong>    RAND</strong>OM;
 +
<strong>    COM</strong>PLEX;
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>TWO</strong>LEVEL;
 +
<strong>    BAS</strong>IC;
 +
<strong>    RAND</strong>OM;
 +
<strong>    MIX</strong>TURE;
 +
<strong>    COM</strong>PLEX;
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>THREE</strong>LEVEL;
 +
<strong>    BAS</strong>IC;
 +
<strong>    RAND</strong>OM;
 +
<strong>    COM</strong>PLEX;
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>CROSS</strong>CLASSIFIED;
 +
<strong>    RAND</strong>OM;
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | EFA # #;
 +
<strong>    BAS</strong>IC;
 +
<strong>    MIX</strong>TURE;
 +
<strong>    COM</strong>PLEX;
 +
<strong>    TWO</strong>LEVEL;
 +
EFA # # UW* # # UB*;
 +
EFA # # UW # # UB;
 +
| width="120" |
 +
|-
 +
| width="168" | ESTIMATOR =
 +
| width="294" | ML;
 +
| width="120" | depends on
 +
|-
 +
| width="168" |
 +
| width="294" | MLM;
 +
| width="120" | analysis type
 +
|-
 +
| width="168" |
 +
| width="294" | MLMV;
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | MLR;
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | MLF;
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | MUML;
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | WLS;
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | WLSM;
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | WLSMV;
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | ULS;
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | ULSMV;
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | GLS;
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | BAYES;
 +
| width="120" |
 +
|-
 +
| width="168" | MODEL =
 +
| width="294" | <strong>CONFIG</strong>URAL;
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | METRIC;
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | SCALAR;
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>NOMEAN</strong>STRUCTURE;
 +
| width="120" | means
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>NOCOV</strong>ARIANCES;
 +
| width="120" | covariances
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>ALL</strong>FREE;
 +
| width="120" | equal
 +
|-
 +
| width="168" | ALIGNMENT =
 +
| width="294" | FIXED;
 +
| width="120" | last class
 +
|-
 +
| width="168" |
 +
| width="294" |
 +
| width="120" | CONFIGURAL
 +
|-
 +
| width="168" |
 +
| width="294" | FIXED (reference class <strong>CONFIG</strong>URAL);
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | FIXED (reference class BSEM);
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | FREE;
 +
| width="120" | last class
 +
|-
 +
| width="168" |
 +
| width="294" |
 +
| width="120" | CONFIGURAL
 +
|-
 +
| width="168" |
 +
| width="294" | FREE (reference class <strong>CONFIG</strong>URAL);
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | FREE (reference class BSEM);
 +
| width="120" |
 +
|-
 +
| width="168" | DISTRIBUTION =
 +
| width="294" | <strong>NORM</strong>AL;
 +
| width="120" | NORMAL
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>SKEW</strong>NORMAL;
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>TDIST</strong>RIBUTION;
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | SKEWT;
 +
| width="120" |
 +
|-
 +
| width="168" | PARAMETERIZATION =
 +
| width="294" | DELTA;
 +
| width="120" | DELTA
 +
|-
 +
| width="168" |
 +
| width="294" | THETA;
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | LOGIT;
 +
| width="120" | LOGIT
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>LOGLIN</strong>EAR;
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>PROB</strong>ABILITY;
 +
<strong>RESCOV</strong>ARIANCES;
 +
| width="120" | 
 +
RESCOV
 +
|-
 +
| width="168" | LINK =
 +
| width="294" | <strong>LOG</strong>IT;
 +
| width="120" | LOGIT
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>PROB</strong>IT;
 +
| width="120" |
 +
|-
 +
| width="168" | ROTATION =
 +
| width="294" | <strong>GEO</strong>MIN;
 +
| width="120" | GEOMIN (OBLIQUE value)
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>GEO</strong>MIN (<strong>OB</strong>LIQUE value);
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>GEO</strong>MIN (<strong>OR</strong>THOGONAL value);
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>QUART</strong>IMIN;
 +
| width="120" | OBLIQUE
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>CF-V</strong>ARIMAX;
 +
| width="120" | OBLIQUE
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>CF-V</strong>ARIMAX (<strong>OB</strong>LIQUE);
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>CF-V</strong>ARIMAX (<strong>OR</strong>THOGONAL);
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>CF-Q</strong>UARTIMAX;
 +
| width="120" | OBLIQUE
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>CF- Q</strong>UARTIMAX (<strong>OB</strong>LIQUE);
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>CF- Q</strong>UARTIMAX (<strong>OR</strong>THOGONAL);
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>CF-E</strong>QUAMAX;
 +
| width="120" | OBLIQUE
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>CF- E</strong>QUAMAX (<strong>OB</strong>LIQUE);
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>CF- E</strong>QUAMAX (<strong>OR</strong>THOGONAL);
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>CF-P</strong>ARSIMAX;
 +
| width="120" | OBLIQUE
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>CF- P</strong>ARSIMAX (<strong>OB</strong>LIQUE);
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>CF- P</strong>ARSIMAX (<strong>OR</strong>THOGONAL);
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>CF-F</strong>ACPARSIM;
 +
| width="120" | OBLIQUE
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>CF- F</strong>ACPARSIM (<strong>OB</strong>LIQUE);
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>CF- F</strong>ACPARSIM (<strong>OR</strong>THOGONAL);
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>CRAW</strong>FER;
 +
| width="120" | OBLIQUE 1/p
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>CRAW</strong>FER (<strong>OB</strong>LIQUE value);
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>CRAW</strong>FER (<strong>OR</strong>THOGONAL value);
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>OBLIM</strong>IN;
 +
| width="120" | OBLIQUE 0
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>OBLIM</strong>IN (<strong>OB</strong>LIQUE value);
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>OBLIM</strong>IN (<strong>OR</strong>THOGONAL value);
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>VAR</strong>IMAX;
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>PRO</strong>MAX;
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>TAR</strong>GET;
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>BI-GEO</strong>MIN;
 +
| width="120" | OBLIQUE
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>BI-GEO</strong>MIN (<strong>OB</strong>LIQUE);
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>BI-GEO</strong>MIN (<strong>OR</strong>THOGONAL);
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>BI-CF-Q</strong>UARTIMAX;
 +
| width="120" | OBLIQUE
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>BI-CF-Q</strong>UARTIMAX (<strong>OB</strong>LIQUE);
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>BI-CF-Q</strong>UARTIMAX (<strong>OR</strong>THOGONAL);
 +
| width="120" |
 +
|-
 +
| width="168" | ROWSTANDARDIZATION =
 +
| width="294" | <strong>CORR</strong>ELATION;
 +
| width="120" | CORRELATION
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>KAIS</strong>ER;
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>COVA</strong>RIANCE;
 +
| width="120" |
 +
|-
 +
| width="168" | PARALLEL =
 +
| width="294" | number;
 +
| width="120" | 0
 +
|-
 +
| width="168" | REPSE =
 +
| width="294" | <strong>BOOT</strong>STRAP;
 +
<strong>JACK</strong>KNIFE;
 +
<strong>JACK</strong>KNIFE<strong>1</strong>;
 +
<strong>JACK</strong>KNIFE<strong>2</strong>;
 +
BRR;
 +
FAY (#);
 +
| width="120" | 
 +
 
 +
 
 +
 
 +
.3
 +
|-
 +
| width="168" | BASEHAZARD =
 +
| width="294" | ON;
 +
OFF;
 +
ON (<strong>EQ</strong>UAL);
 +
ON (<strong>UNEQ</strong>UAL);
 +
OFF (<strong>EQ</strong>UAL);
 +
OFF (<strong>UNEQ</strong>UAL);
 +
| width="120" | depends on
 +
analysis type
 +
EQUAL
 +
 
 +
EQUAL
 +
|-
 +
| width="168" | CHOLESKY =
 +
| width="294" | ON;
 +
OFF;
 +
| width="120" | depends on
 +
analysis type
 +
|-
 +
| width="168" | ALGORITHM =
 +
| width="294" | EM;
 +
| width="120" | depends on
 +
|-
 +
| width="168" |
 +
| width="294" | EMA;
 +
| width="120" | analysis type
 +
|-
 +
| width="168" |
 +
| width="294" | FS;
 +
ODLL;
 +
<strong>INT</strong>EGRATION;
 +
| width="120" |
 +
|-
 +
| width="168" | INTEGRATION =
 +
| width="294" | number of integration points;
 +
<strong>STAND</strong>ARD (number of integration points) ;
 +
 
 +
<strong>GAUSS</strong>HERMITE (number of integration points) ;
 +
<strong>MONTE</strong>CARLO (number of integration points);
 +
| width="120" | STANDARD
 +
depends on
 +
analysis type
 +
15
 +
 
 +
depends on
 +
analysis type
 +
|-
 +
| width="168" | MCSEED =
 +
| width="294" | random seed for Monte Carlo integration;
 +
| width="120" | 0
 +
|-
 +
| width="168" | ADAPTIVE =
 +
| width="294" | ON;
 +
OFF;
 +
| width="120" | ON
 +
|-
 +
| width="168" | INFORMATION =
 +
| width="294" | <strong>OBS</strong>ERVED;
 +
| width="120" | depends on
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>EXP</strong>ECTED;
 +
| width="120" | analysis type
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>COMB</strong>INATION;
 +
| width="120" |
 +
|-
 +
| width="168" | BOOTSTRAP =
 +
| width="294" | number of bootstrap draws;
 +
number of bootstrap draws (<strong>STAND</strong>ARD);
 +
number of bootstrap draws (<strong>RES</strong>IDUAL):
 +
| width="120" | STANDARD
 +
|-
 +
| width="168" | LRTBOOTSTRAP =
 +
| width="294" | number of bootstrap draws for TECH14;
 +
| width="120" | depends on
 +
analysis type
 +
|-
 +
| width="168" | STARTS =
 +
| width="294" | number of initial stage starts and number of final stage optimizations;
 +
| width="120" | depends on
 +
analysis type
 +
|-
 +
| width="168" | STITERATIONS =
 +
| width="294" | number of initial stage iterations;
 +
| width="120" | 10
 +
|-
 +
| width="168" | STCONVERGENCE =
 +
| width="294" | initial stage convergence criterion;
 +
| width="120" | 1
 +
|-
 +
| width="168" | STSCALE =
 +
| width="294" | random start scale;
 +
| width="120" | 5
 +
|-
 +
| width="168" | STSEED =
 +
| width="294" | random seed for generating random starts;
 +
| width="120" | 0
 +
|-
 +
| width="168" | OPTSEED =
 +
| width="294" | random seed for analysis;
 +
| width="120" |
 +
|-
 +
| width="168" | K-1STARTS =
 +
| width="294" | number of initial stage starts and number of final stage optimizations for the k-1 class model for TECH14;
 +
| width="120" | 20 4
 +
|-
 +
| width="168" | LRTSTARTS =
 +
| width="294" | number of initial stage starts and number of final stage optimizations for TECH14;
 +
| width="120" | 0 0 40 8
 +
|-
 +
| width="168" | RSTARTS =
 +
| width="294" | number of random starts for the rotation algorithm and number of factor solutions printed for exploratory factor analysis;
 +
| width="120" | depends on
 +
analysis type
 +
|-
 +
| width="168" | ASTARTS =
 +
| width="294" | number of random starts for the alignment
 +
optimization;
 +
| width="120" | 30
 +
|-
 +
| width="168" | H1STARTS =
 +
| width="294" | Number of initial stage starts and number of final stage optimizations for the H1 model;
 +
| width="120" | 0 0
 +
|-
 +
| width="168" | DIFFTEST =
 +
| width="294" | file name;
 +
| width="120" |
 +
|-
 +
| width="168" | MULTIPLIER =
 +
| width="294" | file name;
 +
| width="120" |
 +
|-
 +
| width="168" | COVERAGE =
 +
| width="294" | minimum covariance coverage with missing data;
 +
| width="120" | .10
 +
|-
 +
| width="168" | ADDFREQUENCY =
 +
| width="294" | value divided by sample size to add to cells with zero frequency;
 +
| width="120" | .5
 +
|-
 +
| width="168" | ITERATIONS =
 +
| width="294" | maximum number of iterations for the Quasi-Newton algorithm for continuous outcomes;
 +
| width="120" | 1000
 +
|-
 +
| width="168" | SDITERATIONS =
 +
| width="294" | maximum number of steepest descent iterations for the Quasi-Newton algorithm for continuous outcomes;
 +
| width="120" | 20
 +
|-
 +
| width="168" | H1ITERATIONS =
 +
| width="294" | maximum number of iterations for unrestricted model with missing data;
 +
| width="120" | 2000
 +
|-
 +
| width="168" | MITERATIONS =
 +
| width="294" | number of iterations for the EM algorithm;
 +
| width="120" | 500
 +
|-
 +
| width="168" | MCITERATIONS =
 +
| width="294" | number of iterations for the M step of the EM algorithm for categorical latent variables;
 +
| width="120" | 1
 +
|-
 +
| width="168" | MUITERATIONS =
 +
| width="294" | number of iterations for the M step of the EM algorithm for censored, categorical, and count outcomes;
 +
| width="120" | 1
 +
|-
 +
| width="168" | RITERATIONS =
 +
| width="294" | maximum number of iterations in the rotation algorithm for exploratory factor analysis;
 +
| width="120" | 10000
 +
|-
 +
| width="168" | AITERATIONS =
 +
| width="294" | maximum number of iterations in the
 +
| width="120" | 5000
 +
|-
 +
| width="168" |
 +
| width="294" | alignment optimization;
 +
| width="120" |
 +
|-
 +
| width="168" | CONVERGENCE =
 +
| width="294" | convergence criterion for the Quasi-Newton algorithm for continuous outcomes;
 +
| width="120" | depends on
 +
analysis type
 +
|-
 +
| width="168" | H1CONVERGENCE =
 +
| width="294" | convergence criterion for unrestricted model with missing data;
 +
| width="120" | .0001
 +
|-
 +
| width="168" | LOGCRITERION =
 +
| width="294" | likelihood convergence criterion for the EM algorithm;
 +
| width="120" | depends on
 +
analysis type
 +
|-
 +
| width="168" | RLOGCRITERION =
 +
| width="294" | relative likelihood convergence criterion for the EM algorithm;
 +
| width="120" | depends on
 +
analysis type
 +
|-
 +
| width="168" | MCONVERGENCE =
 +
| width="294" | convergence criterion for the EM algorithm;
 +
| width="120" | depends on
 +
analysis type
 +
|-
 +
| width="168" | MCCONVERGENCE =
 +
| width="294" | convergence criterion for the M step of the EM algorithm for categorical latent variables;
 +
| width="120" | .000001
 +
|-
 +
| width="168" | MUCONVERGENCE =
 +
| width="294" | convergence criterion for the M step of the EM algorithm for censored, categorical, and count outcomes;
 +
| width="120" | .000001
 +
|-
 +
| width="168" | RCONVERGENCE =
 +
| width="294" | convergence criterion for the rotation algorithm for exploratory factor analysis;
 +
| width="120" | .00001
 +
|-
 +
| width="168" | ACONVERGENCE =
 +
| width="294" | convergence criterion for the derivatives of
 +
the alignment optimization;.
 +
| width="120" | .001
 +
|-
 +
| width="168" | MIXC =
 +
| width="294" | <strong>ITER</strong>ATIONS;
 +
| width="120" | ITERATIONS
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>CONV</strong>ERGENCE;
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | M step iteration termination based on number of iterations or convergence for categorical latent variables;
 +
| width="120" |
 +
|-
 +
| width="168" | MIXU =
 +
| width="294" | <strong>ITER</strong>ATIONS;
 +
| width="120" | ITERATIONS
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>CONV</strong>ERGENCE;
 +
| width="120" |
 +
|-
 +
| width="168" |
 +
| width="294" | M step iteration termination based on number of iterations or convergence for censored, categorical, and count outcomes;
 +
| width="120" |
 +
|-
 +
| width="168" | LOGHIGH =
 +
| width="294" | max value for logit thresholds;
 +
| width="120" | +15
 +
|-
 +
| width="168" | LOGLOW =
 +
| width="294" | min value for logit thresholds;
 +
| width="120" | - 15
 +
|-
 +
| width="168" | UCELLSIZE =
 +
| width="294" | minimum expected cell size;
 +
| width="120" | .01
 +
|-
 +
| width="168" | VARIANCE =
 +
| width="294" | minimum variance value;
 +
| width="120" | .0001
 +
|-
 +
| width="168" | SIMPLICITY =
 +
| width="294" | SQRT;
 +
| width="120" | SQRT
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>FOUR</strong>THRT;
 +
| width="120" |
 +
|-
 +
| width="168" | TOLERANCE =
 +
| width="294" | simplicity tolerance value;
 +
| width="120" | .0001
 +
|-
 +
| width="168" | METRIC=
 +
| width="294" | <strong>REFG</strong>ROUP;
 +
| width="120" | REFGROUP
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>PROD</strong>UCT;
 +
| width="120" |
 +
|-
 +
| width="168" | MATRIX =
 +
| width="294" | <strong>COVA</strong>RIANCE;
 +
| width="120" | COVARIANCE
 +
|-
 +
| width="168" |
 +
| width="294" | <strong>CORR</strong>ELATION;
 +
| width="120" |
 +
|-
 +
| width="168" | POINT =
 +
| width="294" | <strong>MED</strong>IAN;
 +
MEAN;
 +
MODE;
 +
| width="120" | MEDIAN
 +
|-
 +
| width="168" | CHAINS =
 +
| width="294" | number of MCMC chains;
 +
| width="120" | 2
 +
|-
 +
| width="168" | BSEED =
 +
| width="294" | seed for MCMC random number generation;
 +
| width="120" | 0
 +
|-
 +
| width="168" | STVALUES =
 +
| width="294" | <strong>UNPER</strong>TURBED;
 +
<strong>PERT</strong>URBED;
 +
ML;
 +
| width="120" | UNPERTURBED
 +
|-
 +
| width="168" | MEDIATOR =
 +
| width="294" | <strong>LAT</strong>ENT;
 +
<strong>OBS</strong>ERVED;
 +
| width="120" | depends on
 +
analysis type
 +
|-
 +
| width="168" | ALGORITHM =
 +
| width="294" | GIBBS;
 +
GIBBS (PX1);
 +
GIBBS (PX2);
 +
GIBBS (PX3);
 +
GIBBS (RW);
 +
MH;
 +
| width="120" | GIBBS (PX1)
 +
|-
 +
| width="168" | BCONVERGENCE =
 +
| width="294" | MCMC convergence criterion using Gelman-Rubin PSR;
 +
| width="120" | .05
 +
|-
 +
| width="168" | BITERATIONS =
 +
| width="294" | maximum and minimum number of iterations for each MCMC chain when Gelman-Rubin PSR is used;
 +
| width="120" | 50000 0
 +
|-
 +
| width="168" | FBITERATIONS =
 +
| width="294" | fixed number of iterations for each MCMC chain when Gelman-Rubin PSR is not used;
 +
| width="120" |
 +
|-
 +
| width="168" | THIN =
 +
| width="294" | k where every k-th MCMC iteration is saved;
 +
| width="120" | 1
 +
|-
 +
| width="168" | MDITERATIONS =
 +
| width="294" | maximum number of iterations used to compute the Bayes multivariate mode;
 +
| width="120" | 10000
 +
|-
 +
| width="168" | KOLMOGOROV =
 +
| width="294" | number of draws from the MCMC chains;
 +
| width="120" | 100
 +
|-
 +
| width="168" | PRIOR =
 +
| width="294" | number of draws from the prior distribution;
 +
| width="120" | 1000
 +
|-
 +
| width="168" | INTERACTIVE =
 +
| width="294" | file name;
 +
| width="120" |
 +
|-
 +
| width="168" | PROCESSORS =
 +
| width="294" | # of processors # of threads;
 +
| width="120" | 1 1</tbody>
 +
|}

2017年2月27日 (一) 14:04的版本

ANALYSIS命令语法

ANALYSIS:
TYPE = GENERAL; GENERAL
    BASIC;
    RANDOM;
    COMPLEX;
MIXTURE;

    BASIC;     RANDOM;     COMPLEX;

TWOLEVEL;

    BASIC;     RANDOM;     MIXTURE;     COMPLEX;

THREELEVEL;

    BASIC;     RANDOM;     COMPLEX;

CROSSCLASSIFIED;

    RANDOM;

EFA # #;

    BASIC;     MIXTURE;     COMPLEX;     TWOLEVEL; EFA # # UW* # # UB*; EFA # # UW # # UB;

ESTIMATOR = ML; depends on
MLM; analysis type
MLMV;
MLR;
MLF;
MUML;
WLS;
WLSM;
WLSMV;
ULS;
ULSMV;
GLS;
BAYES;
MODEL = CONFIGURAL;
METRIC;
SCALAR;
NOMEANSTRUCTURE; means
NOCOVARIANCES; covariances
ALLFREE; equal
ALIGNMENT = FIXED; last class
CONFIGURAL
FIXED (reference class CONFIGURAL);
FIXED (reference class BSEM);
FREE; last class
CONFIGURAL
FREE (reference class CONFIGURAL);
FREE (reference class BSEM);
DISTRIBUTION = NORMAL; NORMAL
SKEWNORMAL;
TDISTRIBUTION;
SKEWT;
PARAMETERIZATION = DELTA; DELTA
THETA;
LOGIT; LOGIT
LOGLINEAR;
PROBABILITY;

RESCOVARIANCES;

RESCOV

LINK = LOGIT; LOGIT
PROBIT;
ROTATION = GEOMIN; GEOMIN (OBLIQUE value)
GEOMIN (OBLIQUE value);
GEOMIN (ORTHOGONAL value);
QUARTIMIN; OBLIQUE
CF-VARIMAX; OBLIQUE
CF-VARIMAX (OBLIQUE);
CF-VARIMAX (ORTHOGONAL);
CF-QUARTIMAX; OBLIQUE
CF- QUARTIMAX (OBLIQUE);
CF- QUARTIMAX (ORTHOGONAL);
CF-EQUAMAX; OBLIQUE
CF- EQUAMAX (OBLIQUE);
CF- EQUAMAX (ORTHOGONAL);
CF-PARSIMAX; OBLIQUE
CF- PARSIMAX (OBLIQUE);
CF- PARSIMAX (ORTHOGONAL);
CF-FACPARSIM; OBLIQUE
CF- FACPARSIM (OBLIQUE);
CF- FACPARSIM (ORTHOGONAL);
CRAWFER; OBLIQUE 1/p
CRAWFER (OBLIQUE value);
CRAWFER (ORTHOGONAL value);
OBLIMIN; OBLIQUE 0
OBLIMIN (OBLIQUE value);
OBLIMIN (ORTHOGONAL value);
VARIMAX;
PROMAX;
TARGET;
BI-GEOMIN; OBLIQUE
BI-GEOMIN (OBLIQUE);
BI-GEOMIN (ORTHOGONAL);
BI-CF-QUARTIMAX; OBLIQUE
BI-CF-QUARTIMAX (OBLIQUE);
BI-CF-QUARTIMAX (ORTHOGONAL);
ROWSTANDARDIZATION = CORRELATION; CORRELATION
KAISER;
COVARIANCE;
PARALLEL = number; 0
REPSE = BOOTSTRAP;

JACKKNIFE; JACKKNIFE1; JACKKNIFE2; BRR; FAY (#);


.3

BASEHAZARD = ON;

OFF; ON (EQUAL); ON (UNEQUAL); OFF (EQUAL); OFF (UNEQUAL);

depends on

analysis type EQUAL

EQUAL

CHOLESKY = ON;

OFF;

depends on

analysis type

ALGORITHM = EM; depends on
EMA; analysis type
FS;

ODLL; INTEGRATION;

INTEGRATION = number of integration points;

STANDARD (number of integration points) ;

GAUSSHERMITE (number of integration points) ; MONTECARLO (number of integration points);

STANDARD

depends on analysis type 15

depends on analysis type

MCSEED = random seed for Monte Carlo integration; 0
ADAPTIVE = ON;

OFF;

ON
INFORMATION = OBSERVED; depends on
EXPECTED; analysis type
COMBINATION;
BOOTSTRAP = number of bootstrap draws;

number of bootstrap draws (STANDARD); number of bootstrap draws (RESIDUAL):

STANDARD
LRTBOOTSTRAP = number of bootstrap draws for TECH14; depends on

analysis type

STARTS = number of initial stage starts and number of final stage optimizations; depends on

analysis type

STITERATIONS = number of initial stage iterations; 10
STCONVERGENCE = initial stage convergence criterion; 1
STSCALE = random start scale; 5
STSEED = random seed for generating random starts; 0
OPTSEED = random seed for analysis;
K-1STARTS = number of initial stage starts and number of final stage optimizations for the k-1 class model for TECH14; 20 4
LRTSTARTS = number of initial stage starts and number of final stage optimizations for TECH14; 0 0 40 8
RSTARTS = number of random starts for the rotation algorithm and number of factor solutions printed for exploratory factor analysis; depends on

analysis type

ASTARTS = number of random starts for the alignment

optimization;

30
H1STARTS = Number of initial stage starts and number of final stage optimizations for the H1 model; 0 0
DIFFTEST = file name;
MULTIPLIER = file name;
COVERAGE = minimum covariance coverage with missing data; .10
ADDFREQUENCY = value divided by sample size to add to cells with zero frequency; .5
ITERATIONS = maximum number of iterations for the Quasi-Newton algorithm for continuous outcomes; 1000
SDITERATIONS = maximum number of steepest descent iterations for the Quasi-Newton algorithm for continuous outcomes; 20
H1ITERATIONS = maximum number of iterations for unrestricted model with missing data; 2000
MITERATIONS = number of iterations for the EM algorithm; 500
MCITERATIONS = number of iterations for the M step of the EM algorithm for categorical latent variables; 1
MUITERATIONS = number of iterations for the M step of the EM algorithm for censored, categorical, and count outcomes; 1
RITERATIONS = maximum number of iterations in the rotation algorithm for exploratory factor analysis; 10000
AITERATIONS = maximum number of iterations in the 5000
alignment optimization;
CONVERGENCE = convergence criterion for the Quasi-Newton algorithm for continuous outcomes; depends on

analysis type

H1CONVERGENCE = convergence criterion for unrestricted model with missing data; .0001
LOGCRITERION = likelihood convergence criterion for the EM algorithm; depends on

analysis type

RLOGCRITERION = relative likelihood convergence criterion for the EM algorithm; depends on

analysis type

MCONVERGENCE = convergence criterion for the EM algorithm; depends on

analysis type

MCCONVERGENCE = convergence criterion for the M step of the EM algorithm for categorical latent variables; .000001
MUCONVERGENCE = convergence criterion for the M step of the EM algorithm for censored, categorical, and count outcomes; .000001
RCONVERGENCE = convergence criterion for the rotation algorithm for exploratory factor analysis; .00001
ACONVERGENCE = convergence criterion for the derivatives of

the alignment optimization;.

.001
MIXC = ITERATIONS; ITERATIONS
CONVERGENCE;
M step iteration termination based on number of iterations or convergence for categorical latent variables;
MIXU = ITERATIONS; ITERATIONS
CONVERGENCE;
M step iteration termination based on number of iterations or convergence for censored, categorical, and count outcomes;
LOGHIGH = max value for logit thresholds; +15
LOGLOW = min value for logit thresholds; - 15
UCELLSIZE = minimum expected cell size; .01
VARIANCE = minimum variance value; .0001
SIMPLICITY = SQRT; SQRT
FOURTHRT;
TOLERANCE = simplicity tolerance value; .0001
METRIC= REFGROUP; REFGROUP
PRODUCT;
MATRIX = COVARIANCE; COVARIANCE
CORRELATION;
POINT = MEDIAN;

MEAN; MODE;

MEDIAN
CHAINS = number of MCMC chains; 2
BSEED = seed for MCMC random number generation; 0
STVALUES = UNPERTURBED;

PERTURBED; ML;

UNPERTURBED
MEDIATOR = LATENT;

OBSERVED;

depends on

analysis type

ALGORITHM = GIBBS;

GIBBS (PX1); GIBBS (PX2); GIBBS (PX3); GIBBS (RW); MH;

GIBBS (PX1)
BCONVERGENCE = MCMC convergence criterion using Gelman-Rubin PSR; .05
BITERATIONS = maximum and minimum number of iterations for each MCMC chain when Gelman-Rubin PSR is used; 50000 0
FBITERATIONS = fixed number of iterations for each MCMC chain when Gelman-Rubin PSR is not used;
THIN = k where every k-th MCMC iteration is saved; 1
MDITERATIONS = maximum number of iterations used to compute the Bayes multivariate mode; 10000
KOLMOGOROV = number of draws from the MCMC chains; 100
PRIOR = number of draws from the prior distribution; 1000
INTERACTIVE = file name;
PROCESSORS = # of processors # of threads; 1 1</tbody>
取自“http://www.obhrm.net/index.php?title=Mplus_ANALYSIS&oldid=2155”