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==TITLE==
<pre>TITLE: 标题的具体内容;</pre>

==DATA==
<pre>DATA:
FILE IS              file name;
FORMAT IS            format statement;                                                                            FREE
                     FREE;
TYPE IS              INDIVIDUAL;                                                                                  INDIVIDUAL
                     COVARIANCE;
                     CORRELATION;
                     FULLCOV;
                     FULLCORR;
                     MEANS;
                     STDEVIATIONS;
                     MONTECARLO;
                     IMPUTATION; 
NOBSERVATIONS ARE    number of observations;
NGROUPS =            number of groups;                                                                            1
LISTWISE =           ON;                                                                                          OFF;
                     OFF
SWMATRIX =           file name;
VARIANCES =          CHECK;                                                                                       CHECK
                     NOCHECK;
DATA IMPUTATION:            
     IMPUTE =        names of variables for which missing values will be imputed;      
                     number of imputed data sets;                                                                 5
     NDATASETS =     names of files in which imputed data sets are stored;      
     SAVE =          COVARIANCE;                                                                                  COVARIANCE
     MODEL =         SEQUENTIAL;      
                     REGRESSION;      
     VALUES =        values imputed data can take;                                                                no restrictions
     ROUNDING =      number of decimals for imputed continuous variables;                                         3
                     k where every k-th imputation is saved;                                                      100
     THIN =            
DATA WIDETOLONG:            
     WIDE =          names of old wide format variables;      
     LONG =          names of new long format variables;      
     IDVARIABLE =    name of variable with ID information;      
     REPETITION =    name of variable with repetition information;      
DATA LONGTOWIDE:            
     LONG =          names of old long format variables;      
     WIDE =          names of new wide format variables;      
     IDVARIABLE =    name of variable with ID information;      
     REPETITION =    name of variable with repetition information 
                     (values);                                                                                    0, 1, 2, etc.
DATA TWOPART:                  
     NAMES =         names of variables used to create a set of binary and continuous variables;      
     CUTPOINT =      value used to divide the original variables into a set of  binary and continuous variables;  0                        
     BINARY =        names of new binary variables;      
     CONTINUOUS =    names of new continuous variables;      
     TRANSFORM =     function to use to transform new continuous variables;                                        LOG
DATA MISSING:            
     NAMES =         names of variables used to create a set of binary variables;      
     BINARY =        names of new binary variables;      
     TYPE =          MISSING;      
                     SDROPOUT;      
                     DDROPOUT;      
     DESCRIPTIVE =   sets of variables for additional descriptive statistics separated by the | symbol; 
DATA SURVIVAL:
     NAMES =         names of variables used to create a set of binary event-history variables;
     CUTPOINT =      value used to create a set of binary event-history variables from a set of original variables;
     BINARY =        names of new binary variables;
DATA COHORT:
     COHORT IS       name of cohort variable (values);
     COPATTERN IS    name of cohort/pattern variable (patterns);
     COHRECODE =     (old value = new value);
     TIMEMEASURES =  list of sets of variables separated by the | symbol;
     TNAMES =        list of root names for the sets of variables in TIMEMEASURES separated by the | symbol;</pre>

==VARIABLE==
<pre>VARIABLE:                        
NAMES ARE                names of variables in the data set;      
USEOBSERVATIONS ARE      conditional statement to select observations;                                                all observations in data set
USEVARIABLES ARE         names of analysis variables;                                                                 all variables in NAMES
MISSING ARE              variable (#);      
                         . ;      
                         * ;      
                         BLANK;      
CENSORED ARE             names, censoring type, and inflation status for censored  dependent variables;      
CATEGORICAL ARE          names of binary and ordered categorical (ordinal) dependent variables;      
NOMINAL ARE              names of unordered categorical (nominal) dependent variables;      
COUNT ARE                names of count variables (model);      
DSURVIVAL ARE            names of discrete-time survival variables;      
GROUPING IS              name of grouping variable (labels);      
IDVARIABLE IS            name of ID variable;      
FREQWEIGHT IS            name of frequency (case) weight variable;      
TSCORES ARE              names of observed variables with information on individually-varying times of observation;        
AUXILIARY =              names of auxiliary variables;      
                         names of auxiliary variables (M);      
                         names of auxiliary variables (R3STEP);      
                         names of auxiliary variables (R);      
                         names of auxiliary variables (BCH);      
                         names of auxiliary variables (DU3STEP);      
                         names of auxiliary variables (DCATEGORICAL);      
                         names of auxiliary variables (DE3STEP);      
                         names of auxiliary variables (DCONTINUOUS);      
                         names of auxiliary variables (E);      
CONSTRAINT =             names of observed variables that can be used in the MODEL CONSTRAINT command;      
PATTERN IS               name of pattern variable (patterns);      
STRATIFICATION IS        name of stratification variable;      
CLUSTER IS               name of cluster variables;      
WEIGHT IS                name of sampling weight variable;      
WTSCALE IS               UNSCALED;                                                                                   CLUSTER
                         CLUSTER;      
                         ECLUSTER;      
BWEIGHT                  name of between-level sampling weight variable;      
B2WEIGHT IS              name of the level 2 sampling weight variable;      
B3WEIGHT IS              name of the level 3 sampling weight variable;      
BWTSCALE IS              UNSCALED;                                                                                   SAMPLE
                         SAMPLE;      
REPWEIGHTS ARE           names of replicate weight variables;      
SUBPOPULATION IS         conditional statement to select subpopulation;                                              all observations in data set
FINITE =                 name of  variable;                                                                        FPC
                         name of variable (FPC);      
                         name of variable (SFRACTION);      
                         name of variable (POPULATION);      
CLASSES =                names of categorical latent variables (number of latent classes);      
KNOWNCLASS =             name of categorical latent variable with known class membership (labels);      
TRAINING =               names of training variables;                                                                MEMBERSHIP
                         names of variables (MEMBERSHIP);      
                         names of variables (PROBABILITIES);      
                         names of variables (PRIORS);      
WITHIN ARE               names of individual-level observed variables;      
WITHIN ARE (label)       names of individual-level observed variables;      
            
BETWEEN ARE              names of cluster-level observed variables;      
BETWEEN ARE (label)      names of cluster-level observed variables;      
SURVIVAL ARE             names and time intervals for time-to-event variables;      
TIMECENSORED ARE         names and values of variables that contain right censoring information;                    (0 = NOT   1 = RIGHT)</pre>

==DEFINE==
<pre>DEFINE:	
	variable = mathematical expression;
	IF (conditional statement) THEN transformation statements;
	_MISSING
	variable = MEAN (list of variables);
	variable = SUM (list of variables);
	CUT variable or list of variables (cutpoints);
	variable = CLUSTER_MEAN (variable);
	CENTER variable or list of variables (GRANDMEAN);
	CENTER variable or list of variables (GROUPMEAN);
	CENTER variable or list of variables (GROUPMEAN label);
	STANDARDIZE variable or list of variables;
	DO (#, #) expression;</pre>

==ANALYSIS==
ANALYSIS命令有77条子命令。HTML版请访问：http://www.statmodel.com/HTML_UG/chapter16V8.htm

* TYPE =

* ESTIMATOR =

* MODEL =

* ALIGNMENT =

* DISTRIBUTION =

* PARAMETERIZATION =

* LINK =

* ROTATION =

* ROWSTANDARDIZATION =

* PARALLEL =

* REPSE =

* BASEHAZARD =

* CHOLESKY =

* ALGORITHM =

* INTEGRATION =

* MCSEED =

* ADAPTIVE =

* INFORMATION =

* BOOTSTRAP =

* LRTBOOTSTRAP =

* STARTS =

* STITERATIONS =

* STCONVERGENCE =

* STSCALE =

* STSEED =

* OPTSEED =

* K-1STARTS =

* LRTSTARTS =

* RSTARTS =

* ASTARTS =

* H1STARTS =

* DIFFTEST =

* MULTIPLIER =

* COVERAGE =

* ADDFREQUENCY =

* ITERATIONS =

* SDITERATIONS =

* H1ITERATIONS =

* MITERATIONS =

* MCITERATIONS =

* MUITERATIONS =

* RITERATIONS =

* AITERATIONS =

* CONVERGENCE =

* H1CONVERGENCE =

* LOGCRITERION =

* RLOGCRITERION =

* MCONVERGENCE =

* MCCONVERGENCE =

* MUCONVERGENCE =

* RCONVERGENCE =

* ACONVERGENCE =

* MIXC =

* MIXU =

* LOGHIGH =

* LOGLOW =

* UCELLSIZE =

* VARIANCE  =

* SIMPLICITY =

* TOLERANCE =

* METRIC=

* MATRIX =

* POINT =

* CHAINS =

* BSEED =

* STVALUES =

* MEDIATOR =

* ALGORITHM =

* BCONVERGENCE =

* BITERATIONS =

* FBITERATIONS =

* THIN =

* MDITERATIONS =

* KOLMOGOROV =

* PRIOR =

* INTERACTIVE =

* PROCESSORS =

==MODEL==
<pre>MODEL:      
BY                           short for measured by -- defines latent variables. example:  f1 BY y1-y5;
ON                           short for regressed on -- defines regression relationships. example:  f1 ON x1-x9;
PON                          short for regressed on -- defines paired regression relationships. example:  f2  f3 PON f1 f2;
WITH                         short for correlated with -- defines correlational relationships.example:  f1 WITH f2;
PWITH                        short for correlated with -- defines paired correlational relationships. example:  f1 f2 f3 PWITH f4 f5 f6;
list of variables;           refers to variances and residual variances. example:  f1 y1-y9;
[list of variables];         refers to means, intercepts, thresholds. example:  [f1, y1-y9];
*                            frees a parameter at a default value or a specific starting value. example:  y1* y2*.5;
@                            fixes a parameter at a default value or a specific value. example:  y1@ y2@0;
(number)                     constrains parameters to be equal. example:  f1 ON x1 (1); f2 ON x2 (1);
variable$number              label for the threshold of a variable
variable#number              label for nominal observed or categorical latent variable
variable#1                   label for censored or count inflation variable
variable#number              label for baseline hazard parameters
variable#number              label for a latent class
(name)                       label for a parameter
{list of variables};         refers to scale factors. example:  {y1-y9};
|                            names and defines random effect variables. example: s | y1 ON x1;
AT                           short for measured at -- defines random effect variables. example: s | y1-y4 AT t1-t4;
XWITH                        defines interactions between variables;
MODEL INDIRECT:              describes the relationships for which indirect and total effects are requested
      IND                    describes a specific indirect effect or a set of indirect effects when there is no moderation;
      VIA                    describes  a set of indirect effects that includes specific mediators;
      MOD                    describes a specific indirect effect when there is moderation;
MODEL CONSTRAINT:            describes linear and non-linear constraints on parameters
     NEW                     assigns labels to parameters not in the analysis model;
     DO                      describes a do loop or double do loop;
     PLOT                    describes y-axis variables;
     LOOP                    describes x-axis variables;
MODEL TEST:                  describes restrictions on the analysis model for the Wald test
     DO                      describes a do loop or double do loop;
MODEL PRIORS:                specifies the prior distribution for the parameters
     COVARIANCE              assigns a prior to the covariance between two parameters;
     DO                      describes a do loop or double do loop;
     DIFFERENCE              assigns priors to differences between parameters;
MODEL:                       describes the analysis model
MODEL label:                 describes the group-specific model in multiple group analysis and the model for each categorical latent variable and combinations of categorical latent variables in mixture modeling
MODEL:       
     %OVERALL%              describes the overall part of a mixture model
     %class label%          describes the class-specific part of a mixture model
MODEL:          
     %WITHIN%               describes the individual-level model
     %BETWEEN%              describes the cluster-level model for a two-level model
     %BETWEEN label%        describes the cluster-level model for a three-level or cross-classified model
MODEL POPULATION:            describes the data generation model
MODEL POPULATION-label:      describes the group-specific data generation model in multiple group analysis and the data generation model for each categorical latent variable and combinations of categorical latent variables in mixture modeling
MODEL POPULATION:      
     %OVERALL%              describes the overall data generation model for a  mixture model
     %class label%          describes the class-specific data generation model for a mixture model              
MODEL POPULATION:      
     %WITHIN%               describes the individual-level data generation model for a multilevel model
     %BETWEEN%              describes the cluster-level data generation model for a two-level model
     %BETWEEN label%        describes the cluster-level data generation model for a three-level or cross-classified model             
MODEL COVERAGE:              describes the population parameter values for a Monte Carlo study
MODEL COVERAGE-label:        describes the group-specific population parameter values in multiple group analysis and the population parameter values for each categorical latent variable and combinations of categorical latent variables in mixture modeling for a Monte Carlo study
MODEL COVERAGE:      
     %OVERALL%              describes the overall population parameter values of a mixture model for a Monte Carlo study
     %class label%          describes the class-specific population parameter values of a mixture model     
MODEL COVERAGE:      
     %WITHIN%               describes the individual-level population parameter values for coverage
     %BETWEEN%              describes the cluster-level population parameter values for a two-level model for coverage
     %BETWEEN label%        describes the cluster-level population parameter values for a three-level or cross-classified model for coverage            
MODEL MISSING:               describes the missing data generation model for a Monte Carlostudy
MODEL MISSING-label:         describes the group-specific missing data generation model for aMonte Carlo study
MODEL MISSING:        
     %OVERALL%              describes the overall data generation model of a mixture model
     %class label%          describes the class-specific data generation model of a mixture model</pre>

==OUTPUT==
<pre>OUTPUT:		
	SAMPSTAT;
	CROSSTABS;                               ALL
	CROSSTABS (ALL);
	CROSSTABS (COUNT);
	CROSSTABS (%ROW);
	CROSSTABS (%COLUMN);
	CROSSTABS (%TOTAL);
	STANDARDIZED;                            ALL
	STANDARDIZED (ALL);
	STANDARDIZED (STDYX);
	STANDARDIZED (STDY);
	STANDARDIZED (STD);
	RESIDUAL;
	MODINDICES (minimum chi-square);10
	MODINDICES (ALL);
	MODINDICES (ALL minimum chi-square);10
	CINTERVAL;                               SYMMETRIC
	CINTERVAL (SYMMETRIC);
	CINTERVAL (BOOTSTRAP);
	CINTERVAL (BCBOOTSTRAP);
	CINTERVAL (EQTAIL);                      EQTAIL
	CINTERVAL (HPD);
	SVALUES;
	NOCHISQUARE;
	NOSERROR;
	H1SE;
	H1TECH3;
	H1MODEL;                                 COVARIANCE
	H1MODEL (COVARIANCE);
	H1MODEL (SEQUENTIAL);
	PATTERNS;
	FSCOEFFICIENT;
	FSDETERMINACY;
	BASEHAZARD;
	LOGRANK;
	ALIGNMENT;
	ENTROPY;
	TECH1;
	TECH2;
	TECH3;
	TECH4;
	TECH5;
	TECH6;
	TECH7;
	TECH8;
	TECH9;
	TECH10;
	TECH11;
	TECH12;
	TECH13;
	TECH14;
	TECH15;
	TECH16;</pre>

==SAVEDATA==
<pre>SAVEDATA:		
FILE IS          file name;
FORMAT IS      	 format statement;   	               F10.3
	         FREE;
MISSFLAG =    	 missing value flag;   	               *
RECORDLENGTH IS  characters per record;                1000	
SAMPLE IS	 file name;
COVARIANCE IS	 file name;
SIGBETWEEN IS	 file name;
SWMATRIX IS	 file name;
RESULTS ARE	 file name;
ESTIMATES ARE	 file name;
DIFFTEST IS	 file name;
TECH3 IS	 file name;
TECH4 IS	 file name;
KAPLANMEIER IS	 file name;
BASEHAZARD IS	 file name;
ESTBASELINE IS 	 file name;
RESPONSE IS	 file name;
MULTIPLIER IS	 file name;
BPARAMETERS IS	 file name;
RANKING IS	 file name;
TYPE IS   	 COVARIANCE;   	                       varies
	         CORRELATION;				
SAVE =	         FSCORES;
         	 FSCORES (#);
	         LRESPONSES (#);
         	 CPROBABILITIES;
         	 REPWEIGHTS;
	         MAHALANOBIS;
         	 LOGLIKELIHOOD;
         	 INFLUENCE;
	         COOKS;
	         BCHWEIGHTS;
FACTORS =	 names of factors;
LRESPONSES =	 names of latent response variables;	
MFILE =          file name;
MNAMES =	 names of variables in the data set;   	
MFORMAT =	 format statement;   	               FREE
	         FREE;
MMISSING =	 Variable (#);
          	 *;
	         .;
MSELECT =	 names of variables;   	               all variables in MNAMES</pre>

==PLOT==
<pre>PLOT:		     		
TYPE IS	        PLOT1;	
	        PLOT2;	
	        PLOT3;	
SERIES IS	list of variables in a series plus x-axis values;	
FACTORS ARE	names of factors (#);	
LRESPONSES ARE	names of latent response variables (#);	
OUTLIERS ARE	MAHALANOBIS;	
	        LOGLIKELIHOOD;	
	        INFLUENCE;	
	        COOKS;	
MONITOR IS	ON;	                                               OFF
	        OFF;</pre>

==MONTECARLO==
<pre>MONTECARLO:				
NAMES =	         names of variables;
NOBSERVATIONS =  number of observations;
NGROUPS =	 number of groups;                                                                          1
NREPS =	         number of  replications;                                                                   1
SEED =	         random seed for data generation;                                                           0
GENERATE =	 scale of dependent variables for data generation;
CUTPOINTS =	 thresholds to be used for categorization of covariates;
GENCLASSES =	 names of categorical latent variables (number of latent classes used for data generation);
NCSIZES =	 number of unique cluster sizes for each group separated by the | symbol;
CSIZES =	 number (cluster size) for each group separated by the | symbol;
HAZARDC =	 specifies the hazard for the censoring process;
PATMISS =	 missing data patterns and proportion missing for each dependent variable;
PATPROBS =	 proportion for each missing data pattern;
MISSING =	 names of dependent variables that have missing data;
CENSORED ARE	 names and limits of censored-normal  dependent variables;
CATEGORICAL ARE	 names of ordered categorical dependent variables;
NOMINAL ARE	 names of unordered categorical dependent variables;
COUNT ARE	 names of count variables;
CLASSES =	 names of categorical latent variables (number of latent classes used for model estimation);
AUXILIARY =	 names of auxiliary variables (R3STEP);
                 names of auxiliary variables (R);
                 names of auxiliary variables (BCH);
                 names of auxiliary variables (DU3STEP);
                 names of auxiliary variables (DCATEGORICAL);
	         names of auxiliary variables (DE3STEP);
                 names of auxiliary variables (DCONTINUOUS);
	         names of auxiliary variables (E);
SURVIVAL =       names and time intervals for time-to-event variables;
TSCORES =	 names, means, and standard deviations of observed variables with information on individually-varying times of observation;
WITHIN =	 names of individual-level observed variables;
BETWEEN =	 names of cluster-level observed variables;
POPULATION =	 name of file containing population parameter values for data generation;
COVERAGE =	 name of file containing population parameter values for computing parameter coverage;
STARTING =	 name of file containing parameter values for use as starting values for the analysis;
REPSAVE =	 numbers of the replications to save data from or ALL;
SAVE =	         name of file in which generated data are stored;
RESULTS =	 name of file in which analysis results are stored;
BPARAMETERS =	 name of file in which Bayesian posterior parameter values are stored;	</pre>