查看“Mplus ANALYSIS”的源代码

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!ANALYSIS:
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|TYPE =
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|GENERAL;
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|GENERAL
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|      BASIC;
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|      RANDOM;
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|      COMPLEX;
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|MIXTURE;
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|      BASIC;
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|      RANDOM;
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|      COMPLEX;
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|TWOLEVEL;
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|      BASIC;
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|      RANDOM;
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|      MIXTURE;
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|      COMPLEX;
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|THREELEVEL;
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|      BASIC;
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|      RANDOM;
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|      COMPLEX;   
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|CROSSCLASSIFIED;
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|       RANDOM;
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|EFA  #   #;
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|      BASIC;
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|      MIXTURE;
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|      COMPLEX;
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|      TWOLEVEL;
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|            EFA #  #  UW* #  #  UB*;
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|            EFA #  #  UW #  #  UB;
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|ESTIMATOR =
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|ML;
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|depends on
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|MLM;
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|analysis type
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|MLMV;
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|MLR;
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|MLF;
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|MUML;
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|WLS;
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|WLSM;
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|WLSMV;
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|ULS;
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|ULSMV;
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|GLS;
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|BAYES;
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|MODEL =
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|CONFIGURAL;
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|METRIC;
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|SCALAR;
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|NOMEANSTRUCTURE;
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|means
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|NOCOVARIANCES;
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|covariances
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|ALLFREE;
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|equal
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|ALIGNMENT =
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|FIXED;
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|last class
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|CONFIGURAL
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|FIXED (reference class CONFIGURAL);
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|FIXED (reference class BSEM);
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|FREE;
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|last class
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|CONFIGURAL
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|FREE (reference class CONFIGURAL);
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|FREE (reference class BSEM);
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|DISTRIBUTION =
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|NORMAL;
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|NORMAL
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|SKEWNORMAL;
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|TDISTRIBUTION;
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|SKEWT;
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|PARAMETERIZATION =
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|DELTA;
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|DELTA
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|THETA;
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|LOGIT;
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|LOGIT
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|LOGLINEAR;
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|PROBABILITY;
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|RESCOVARIANCES;
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|RESCOV
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|LINK =
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|LOGIT;
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|LOGIT
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|PROBIT;
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|ROTATION =
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|GEOMIN;
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|GEOMIN (OBLIQUE value)
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|GEOMIN (OBLIQUE value);
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|GEOMIN (ORTHOGONAL value);
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|QUARTIMIN;
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|OBLIQUE
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|CF-VARIMAX;
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|OBLIQUE
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|CF-VARIMAX (OBLIQUE);
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|CF-VARIMAX (ORTHOGONAL);
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|CF-QUARTIMAX;
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|OBLIQUE
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|CF- QUARTIMAX (OBLIQUE);
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|CF- QUARTIMAX (ORTHOGONAL);
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|CF-EQUAMAX;
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|OBLIQUE
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|CF- EQUAMAX (OBLIQUE);
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|CF- EQUAMAX (ORTHOGONAL);
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|CF-PARSIMAX;
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|OBLIQUE
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|CF- PARSIMAX (OBLIQUE);
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|CF- PARSIMAX (ORTHOGONAL);
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|CF-FACPARSIM;
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|OBLIQUE
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|CF- FACPARSIM (OBLIQUE);
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|CF- FACPARSIM (ORTHOGONAL);
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|CRAWFER;
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|OBLIQUE 1/p
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|CRAWFER (OBLIQUE value);
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|CRAWFER (ORTHOGONAL value);
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|OBLIMIN;
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|OBLIQUE 0
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|OBLIMIN (OBLIQUE value);
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|OBLIMIN (ORTHOGONAL value);
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|VARIMAX;
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|PROMAX;
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|TARGET;
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|BI-GEOMIN;
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|OBLIQUE
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|BI-GEOMIN (OBLIQUE);
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|BI-GEOMIN (ORTHOGONAL);
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|BI-CF-QUARTIMAX;
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|OBLIQUE
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|BI-CF-QUARTIMAX (OBLIQUE);
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|BI-CF-QUARTIMAX (ORTHOGONAL);
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|ROWSTANDARDIZATION =
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|CORRELATION;
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|CORRELATION
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|KAISER;
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|COVARIANCE;
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|PARALLEL =
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|number;
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|0
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|REPSE =
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|BOOTSTRAP;
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|JACKKNIFE;
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|JACKKNIFE1;
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|JACKKNIFE2;
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|BRR;
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|FAY (#);
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|.3
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|BASEHAZARD =
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|ON;
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|OFF;
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|ON (EQUAL);
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|ON (UNEQUAL);
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|OFF (EQUAL);
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|OFF (UNEQUAL);
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|depends on
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|analysis type
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|EQUAL
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|EQUAL
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|CHOLESKY =
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|ON;
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|OFF;
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|depends on
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|analysis type
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|ALGORITHM =
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|EM;
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|depends on
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|EMA;
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|analysis type
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|FS;
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|ODLL;
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|INTEGRATION;
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|INTEGRATION =
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|number of integration points;
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|STANDARD (number of integration points) ;
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|GAUSSHERMITE (number of integration points) ;
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|MONTECARLO (number of integration points);
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|STANDARD
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|depends on
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|analysis type
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|15
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|depends on
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|analysis type
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|MCSEED =
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|random seed for Monte Carlo integration;
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|0
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|ADAPTIVE =
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|ON;
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|OFF;
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|ON
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|INFORMATION =
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|OBSERVED;
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|depends on
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|EXPECTED;
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|analysis type
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|COMBINATION;
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|BOOTSTRAP =
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|number of bootstrap draws;
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|number of bootstrap draws (STANDARD);
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|number of bootstrap draws (RESIDUAL):
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|STANDARD
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|LRTBOOTSTRAP =
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|number of bootstrap draws for TECH14;
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|depends on
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|analysis type
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|STARTS =
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|number of initial stage starts and number of final stage optimizations;
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|depends on
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|analysis type
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|STITERATIONS =
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|number of initial stage iterations;
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|10
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|STCONVERGENCE =
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|initial stage convergence criterion;
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|1
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|STSCALE =
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|random start scale;
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|5
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|STSEED =
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|random seed for generating random starts;
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|0
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|OPTSEED =
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|random seed for analysis;
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|K-1STARTS =
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|number of initial stage starts and number of final stage optimizations for the k-1 class model for TECH14;
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|20 4
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|LRTSTARTS =
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|number of initial stage starts and number of final stage optimizations for TECH14;
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|0 0 40 8
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|RSTARTS =
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|number of random starts for the rotation algorithm and number of factor solutions printed for exploratory factor analysis;
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|depends on
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|analysis type
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|ASTARTS =
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|number of random starts for the alignment
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|optimization;
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|30
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|H1STARTS =
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|Number of initial stage starts and number of final stage optimizations for the H1 model;
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|0 0
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|DIFFTEST =
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|file name;
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|MULTIPLIER =
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|file name;
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|COVERAGE =
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|minimum covariance coverage with missing data;
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|.10
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|ADDFREQUENCY =
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|value divided by sample size to add to cells with zero frequency;
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|.5
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|ITERATIONS =
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|maximum number of iterations for the Quasi-Newton algorithm for continuous outcomes;
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|1000
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|SDITERATIONS =
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|maximum number of steepest descent iterations for the Quasi-Newton algorithm for continuous outcomes;
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|20
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|H1ITERATIONS =
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|maximum number of iterations for unrestricted model with missing data;
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|2000
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|MITERATIONS =
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|number of iterations for the EM algorithm;
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|500
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|MCITERATIONS =
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|number of iterations for the M step of the EM algorithm for categorical latent variables;
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|1
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|MUITERATIONS =
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|number of iterations for the M step of the EM algorithm for censored, categorical, and count outcomes;
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|1
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|RITERATIONS =
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|maximum number of iterations in the rotation algorithm for exploratory factor analysis;
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|10000
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|AITERATIONS =
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|maximum number of iterations in the
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|5000
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|alignment optimization;
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|CONVERGENCE =
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|convergence criterion for the Quasi-Newton algorithm for continuous outcomes;
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|depends on
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|analysis type
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|H1CONVERGENCE =
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|convergence criterion for unrestricted model with missing data;
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|.0001
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|LOGCRITERION =
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|likelihood convergence criterion for the EM algorithm;
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|depends on
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|analysis type
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|RLOGCRITERION =
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|relative likelihood convergence criterion for the EM algorithm;
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|depends on
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|analysis type
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|MCONVERGENCE =
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|convergence criterion for the EM algorithm;
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|depends on
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|analysis type
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|MCCONVERGENCE =
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|convergence criterion for the M step of the EM algorithm for categorical latent variables;
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|.000001
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|MUCONVERGENCE =
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|convergence criterion for the M step of the EM algorithm for censored, categorical, and count outcomes;
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|.000001
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|RCONVERGENCE =
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|convergence criterion for the rotation algorithm for exploratory factor analysis;
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|.00001
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|ACONVERGENCE =
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|convergence criterion for the derivatives of
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|the alignment optimization;.
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|.001
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|MIXC =
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|ITERATIONS;
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|ITERATIONS
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|CONVERGENCE;
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|M step iteration termination based on number of iterations or convergence for categorical latent variables;
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|MIXU =
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|ITERATIONS;
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|ITERATIONS
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|CONVERGENCE;
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|M step iteration termination based on number of iterations or convergence for censored, categorical, and count outcomes;
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|LOGHIGH =
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|max value for logit thresholds;
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|+15
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|LOGLOW =
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|min value for logit thresholds;
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|- 15
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|UCELLSIZE =
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|minimum expected cell size;
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|.01
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|VARIANCE  =
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|minimum variance value;
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|.0001
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|SIMPLICITY =
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|SQRT;
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|SQRT
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|FOURTHRT;
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|TOLERANCE =
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|simplicity tolerance value;
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|.0001
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|METRIC=
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|REFGROUP;
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|REFGROUP
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|PRODUCT;
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|MATRIX =
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|COVARIANCE;
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|COVARIANCE
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|CORRELATION;
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|POINT =
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|MEDIAN;
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|MEAN;
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|MODE;
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|MEDIAN
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|CHAINS =
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|number of MCMC chains;
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|2
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|BSEED =
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|seed for MCMC random number generation;
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|0
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|STVALUES =
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|UNPERTURBED;
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|PERTURBED;
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|ML;
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|UNPERTURBED
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|MEDIATOR =
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|LATENT;
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|OBSERVED;
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|depends on
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|analysis type
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|ALGORITHM =
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|GIBBS;
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|GIBBS (PX1);
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|GIBBS (PX2);
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|GIBBS (PX3);
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|GIBBS (RW);
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|MH;
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|GIBBS (PX1)
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|BCONVERGENCE =
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|MCMC convergence criterion using Gelman-Rubin PSR;
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|.05
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|BITERATIONS =
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|maximum and minimum number of iterations for each MCMC chain when Gelman-Rubin PSR is used;
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|50000 0
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|FBITERATIONS =
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|fixed number of iterations for each MCMC chain when Gelman-Rubin PSR is not used;
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|THIN =
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|k where every k-th MCMC iteration is saved;
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|1
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|MDITERATIONS =
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|maximum number of iterations used to compute the Bayes multivariate mode;
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|10000
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|KOLMOGOROV =
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|number of draws from the MCMC chains;
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|100
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|PRIOR =
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|number of draws from the prior distribution;
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|1000
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|INTERACTIVE =
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|file name;
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|PROCESSORS =
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|# of processors  # of threads;
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|1 1
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