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META ES BINARY

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} ]

]

* * 如果省略子命令,那么为缺省值。

此命令读取活动数据集并导致执行任何暂挂命令。 请参阅主题命令顺序以获取更多信息。

可以从元分析二元效应大小对话框生成 META ES BINARY 命令的语法。

发布历史

R28.0
  • 已引入命令。

Example


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.

 

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