MCPerm (version 1.1.4)

PermMeta.boxplot: boxplot for the result of 'meta.MCPerm' or 'meta.TradPerm'

Description

boxplot for the result of 'meta.MCPerm' or 'meta.TradPerm'

Usage

PermMeta.boxplot(PermMeta, plot = "Qp", true_data_pch = 3, pch_col = "red",  border_col = "red", fill_col = NULL, 
	 main = "boxplot for heterogeneity Q p_vlaue", digits = 3)

Arguments

PermMeta

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

plot

a character string indicating which return value of function 'meta.TradPerm' or 'meta.MCPerm' to be plot. The value can be "Qp"(default), "I2", "merged_LnOR", "merged_LnOR_VAR" or "merged_LnOR_p". And the value must be simulation data. 'Qp', "I2", "merged_LnOR", "merged_LnOR_VAR" and "merged_LnOR_p" separetly plots the return value 'perm_Qp', 'perm_I2', 'perm_merged_LnOR', 'perm_merged_VARLnOR', 'perm_merged_p'.

true_data_pch

the pch(default 3) to mark the observed value in the boxplot of simulation data.

pch_col

the color(default 'red') of pch.

border_col

the color(default 'red') for the border of boxplot.

fill_col

the filled color(default NULL) for the body of boxplot.

main

the main title (on top), default value is "boxplot for heterogeneity Q p_vlaue".

digits

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

Details

boxplot for the return value('perm_Qp','perm_I2','perm_merged_LnOR','perm_merged_VARLnOR', 'perm_merged_p') of 'meta.MCPerm' or 'meta.TradPerm'. And through 'pch' and text to mark the observed value.

The symbols in the legend: 'Q_stat' is the Q statistic for meta data heterogeneity; 'Q_p' is the p value of Q value(chi square distribution,the number of studies in meta analysis minus one is degree of freedom of Q value.); 'p.corrected' is the corrected p value by permutation; 'I2_stat' is the statistic I2(calculated by formula max(Q-d.f./Q, 0)) for meta data heterogeneity; 'merged_LnOR' is the merged log odd ratio of observed data; 'merged_LnOR_VAR' is the variance of log odd ratio for observed data; 'merged_LnOR_p' is the p value of log odd ratio of observed data which obey normal distribution.

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

See Also

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

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)
## set working directory to save the plots.
# setwd("D:\")
# pdf("PermMeta.boxplot.pdf",height=6,width=6)
# PermMeta.boxplot(result,plot="Qp",
    # true_data_pch=5,pch_col='red',border_col='black',fill_col=NULL,
    # main="boxplot for heterogeneity Q p_vlaue")
# PermMeta.boxplot(result,plot="I2",
    # true_data_pch=5,pch_col="red",border_col='black',fill_col=NULL,
    # main="boxplot plot for heterogeneity I2")
# PermMeta.boxplot(result,plot="merged_LnOR",
    # true_data_pch=5,pch_col="red",border_col='black',fill_col=NULL,
	 # main="boxplot plot for merged_LnOR")
# PermMeta.boxplot(result,plot="merged_LnOR_VAR",
    # true_data_pch=5,pch_col="red",border_col='black',fill_col=NULL,
    # main="boxplot plot for merged_LnOR_VAR")
# PermMeta.boxplot(result,plot="merged_LnOR_p",
    # true_data_pch=5,pch_col="red",border_col='black',fill_col=NULL,
    # main="boxplot plot for merged_LnOR_p")
# dev.off()