MCPerm (version 1.1.4)

PermMeta.LnOR.CDC: cumulative distribution curve for the return value 'perm_LnOR' of 'meta.MCPerm' or 'meta.TradPerm'

Description

cumulative distribution curve for the return value 'perm_LnOR' of 'meta.MCPerm' or 'meta.TradPerm'.

Usage

PermMeta.LnOR.CDC(PermMeta, plot_study = "all", nrow = 2, ncol = 3,  PermMeta.LnOR_pch = 4, PermMeta.LnOR_col = "black", 
	 LnOR_VAR_pch = 18, LnOR_VAR_col = "blue", 
	 VAR_LnOR_pch = 18, VAR_LnOR_col = "red", 
	 main = "cumulative distribution curve for LnOR", title = NULL, 
	 xlab = "LnOR", ylab = "cumulative probability", digits = 3)

Arguments

PermMeta

the result of function 'meta.TradPerm' or 'meta.MCPerm'.

plot_study

a numeric vector indicates which study(ies) in meta analysis to be plotted. Default value is 'all', which indicates all studies in meta analysis to be plotted.

nrow,ncol

positive integer, divides the device up into 'nrow'(default is 2) rows and 'ncol'(default is 3) columns.

PermMeta.LnOR_pch,PermMeta.LnOR_col

the pch(default 4) and the color(default 'black') of pch are for the cumulative distribution curve of the return value 'perm_LnOR' of certain study.

LnOR_VAR_pch,LnOR_VAR_col

the pch(default 18) and the color*(default 'blue') of pch are for the cumulative distribution curve of the normal distrition with mean=0 and variance=1/ai+1/bi+1/ci+1/di.

VAR_LnOR_pch,VAR_LnOR_col

the pch(default 18) and the color(default 'red') of pch are for the cumulative distribution curve of the normal distrition with mean=0 and variance is the variance of simulation log odd ratios.

main

the main title(on top), default value is "cumulative distribution curve for LnOR".

title

the sub main title for each plotted study(on top).

xlab,ylab

X axis label, default value is 'LnOR'. Y axis label, default value is 'cumulative probability'.

digits

integer(default 3) indicating the number of decimal places.

Value

plot_study

the value of paramter 'plot_study'.

LnOR

the numeric vector of log odd ratio of the observed data for the plotted studies.

sample

the numeric vector of sample size of the plotted studies.

LnOR_VAR

the numeric vector of variance of the sencond cure for the plotted studies.

VAR_LnOR

the numeric vector of variance of the third cure for the plotted studies.

Details

Plot three cumulative distribution cures(abbreviation:CDC): 1) CDC for simulative log odd ratios; 2) CDC for normal distribution with mean=0 and var=variance of observed log odd ratio of certain study(1/ai+1/bi+1/ci+1/di); 3) CDC for normal distribution with mean=0 and var=variance of simulative log odd ratios. The symbol---'perm_lnOR','pnorm_LnOR_VAR','pnorm_VAR_LnOR' in the topright legend separately indicated the first, second, third cure. Through three CDC compared, observe than the thrid cure is more corresponding to the first cure when sample size is smaller.

The symbol in the bottomright legend: 'LnOR' indicates the log odd ratio of observed data for the study; 'sample' indicates the sample size of the study; 'LnOR_VAR' indicates the variance of second cure; 'VAR_LnOR' indicates the variance of third cure.

MCPerm details see chisq.MCPerm. TradPerm details see chisq.TradPerm.

See Also

meta.MCPerm, meta.TradPerm, chisq.MCPerm, chisq.TradPerm, VS.CDC, VS.KS, VS.Genotype.CDC, VS.Allele.CDC, PermMeta.LnOR.Hist, PermMeta.LnOR.qqnorm, PermMeta.LnOR.boxplot, PermMeta.Hist, PermMeta.boxplot

Examples

## import data
# data(MetaGenotypeCount)
## delete first line
# temp=MetaGenotypeCount[-1,];
# result=meta.MCPerm(case_11=as.numeric(temp[,14]),case_12=as.numeric(temp[,16]),
	 # case_22=as.numeric(temp[,18]),control_11=as.numeric(temp[,15]),
	 # control_12=as.numeric(temp[,17]),control_22=as.numeric(temp[,19]),
	 # model="allele",fixed_method="MH",random_method="DL",repeatNum=1000)
# PermMeta.LnOR.CDC(result,plot_study=c(3,5,21,7,12,9),nrow=2,ncol=3)