META ES BINARY 在 Statistics Base Edition 中可用。 语法表示在活动数据集中提供预先计算的效应大小数据时二进制结果的元分析过程。
META ES BINARY
[ /CRITERIA
[ SCOPE = {AVAILABLE**} {LISTWISE} ]
[ CLASSMISSING = {EXCLUDE**} {INCLUDE} ]
[ CILEVEL = {95**} {value} ]
[ MAXITER = {100**} {integer} ]
[ MAXSTEP = {5**} {integer} ]
[ CONVERGENCE = {1E-6**} {value} ]
]
/DATA
ES = {variable}
ESTYPE = {LOGOR} {LOGPETO} {LOGRR} {RD}
{VAR = {variable}} {SE = {variable}}
[ ID = {variable} ]
[ STUDY = {variable} ]
[ /ANALYSIS
[ SUBGROUP = {variable} ]
[ CUMULATIVE = {variable}[ (SORT ={ASCENDING**} {DESCENDING}) ] ]
]
[ /INFERENCE
[ MODEL = {RANDOM**} {FIXED} ]
[ ESTIMATE = {REML**} {ML} {BAYES}
{HEDGES} {HUNTER_SCHMIDT} {DERSIMONIAN_LAIRD} {SIDIK_JONKMAN}
]
[ ADJUSTSE = {NONE**} {KNAPP_HARTUNG} {TRUNCATED_KNAPP_HARTUNG} ]
]
[ /CONTRAST
[ VARIABLES = {variable_list} ]
[ COEFFICIENTS = {values} ]
[ EFORM = {FALSE**} {TRUE} ]
]
[ /BIAS
[ COVARIATES = {covariate_list} ]
[ FACTORS = factor_list ]
[ INTERCEPT = {INCLUDE**} {EXCLUDE} ]
[ MULTIPLICATIVE = {FALSE**} {TRUE} ]
[ DISTRIBUTION = {T**} {NORMAL}]
]
[ /TRIMFILL
[ SIDE = {EGGER_SLOPE**} {LEFT} {RIGHT} ]
[ METHOD = {LINEAR**} {RUN} {QUADRATIC} ]
[ MODEL = {RANDOM**} {FIXED} ]
[ ESTIMATE = {REML**} {ML} {BAYES}
{HEDGES} {HUNTER_SCHMIDT} {DERSIMONIAN_LAIRD} {SIDIK_JONKMAN} ]
[ ADJUSTSE = {NONE**} {KNAPP_HARTUNG} {TRUNCATED_KNAPP_HARTUNG} ]
]
[ /PRINT
[ HOMOGENEITY] [ HETEROGENEITY ] [ INDIVIDUAL ] [ CUMULATIVE ] [ PREDICTION ]
[ EFORM({FALSE**} {TRUE}) ]
]
[ /SAVE
[ ES_EXP[(var_name)] ] [ SE_ES[(var_name)] ]
[ CIL_ES[(var_name)] [ CIL_ES_EXP[(var_name)] ]
[ CIU_ES[(var_name)] [ CIU_ES_EXP[(var_name)] ]
[ PVAL_ES[(var_name)] ] [ WEIGHT[(var_name)] ] [ WEIGHT_PCT[(var_name)] ]
]
[ /OUTFILE
CUMSTATS({'savfile'} {dataset})
[ CUMES[(var_name)] ] [ CUMES_EXP[(var_name)] ] [ SE_CUMES[(var_name)] ]\
[ CIL_CUMES[(var_name)] ] [ CIL_CUMES_EXP[(var_name)] ]
[ CIU_CUMES[(var_name)] ] [ CIU_CUMES_EXP[(var_name)] ]
[ PVAL_CUMES[(var_name)] ]
]
[ /FORESTPLOT
[ DISPLAY = {[ES] [SE] [CI] [WEIGHT] [PVAL]} ]
[ EFORM = {FALSE**} {TRUE} ]
[ ADDCOLS = {variable_list} ]
[ POSITION = {RIGHT**} {LEFT} ]
[ SORT = {variable}[({ASCENDING**} {DESCENDING})] ]
[ REFLINES = {[OVERALL] [NULL]} ]
[ ANNOTATIONS = {[HOMOGENEITY] [HETEROGENEITY] [TEST]} ]
[ CROP = {value1 value2} ]
]
[ /CUMFORESTPLOT
[ DISPLAY = {[ES] [SE] [CI] [PVAL]} ]
[ EFORM = {FALSE**} {TRUE} ]
[ ADDCOLS = {variable_list} ]
[ POSITION = {RIGHT**} {LEFT} ]
[ CROP = {value1 value2} ]
]
[ /BUBBLEPLOT
PREDICTORS = {variable_list}
[ CENTER = {FALSE**} {TRUE} ]
[ PROPORTION = {TRUE**} {FALSE} ]
[ FITLINE = {TRUE**} {FALSE} ]
[ CI = {TRUE**} {FALSE} ]
[ LABEL = {variable}[({AUTO**} {RIGHT} {LEFT} {UPPER} {BOTTOM})] ]
[ YRANGE = {value1 value2} ]
[ XRANGE = {value1 value2} ]
]
[ /FUNNELPLOT
[ IMPUTE = {FALSE**} {TRUE[(REFLINE)]} ]
[ YAXIS = {SE**} {INV_SE} {VAR} {INV_VAR} ]
[ LABEL = {variable}[({AUTO**} {RIGHT} {LEFT} {UPPER} {BOTTOM})] ]
[ YRANGE = {value1 value2} ]
[ XRANGE = {value1 value2} ]
]
[ /GALBRAITHPLOT
[ CI = {TRUE**} {FALSE} ]
[ LABEL = {variable}[({AUTO**} {RIGHT} {LEFT} {UPPER} {BOTTOM})] ]
[ YRANGE = {value1 value2} ]
[ XRANGE = {value1 value2} ]
]
META ES BINARY
/DATA ES=var_name SE=var_name ID=var_name ESTYPE=LOGOR
/CRITERIA CILEVEL=95 SCOPE=AVAILABLE CLASSMISSING=EXCLUDE MAXITER=100 MAXSTEP=100
CONVERGENCE=0.000001
/INFERENCE MODEL=RANDOM ESTIMATE=REML ADJUSTSE=NONE.