tigerstats (version 0.3.2)

binomtestGC: Exact Procedures for a Single Proportion

Description

Wrapper for binom.test in package stats. Employs the binomial distribution in inferential procedures for a single proportion.

Usage

binomtestGC(x,data=parent.frame(),n=numeric(),p=NULL,
                         alternative=c("two.sided","less","greater"),
                         success="yes",conf.level=0.95,graph=FALSE,verbose=TRUE)

Arguments

x

Either a formula or a numeric vector. If formula, it must be of the form ~x indicating the single variable under study. When summary data are provided, x is a numeric vector of success counts.

data

Data frame that supplies the variable x. If not found in data, the variable is searched for in the parent environment.

n

When not empty, this is a numeric vector giving the size of the sample.

p

Specifies Null Hypothesis value for population proportion. If not set, no test is performed.

alternative

"two.sided" requests computation of a two-sided P-value; other possible values are "less" and "greater".

success

When x is a formula, this argument indicates which value of variable x is being counted as a success. When working with formula-data input the value of this parameter MUST be set, even when the variable has only two values.

conf.level

Number between 0 and 1 indicating the confidence-level of the interval supplied.

graph

If TRUE, plot graph of P-value. Ignored if no test is performed.

verbose

Determines whether to return lots of information or only the basics

Value

an object of class GCbinomtest.

Examples

# NOT RUN {
#Confidence interval only:
binomtestGC(~sex,data=m111survey,success="female")

#Confidence interval and two-sided test, Null Hypothesis p = 0.5:
binomtestGC(~sex,data=m111survey,success="female",p=0.5)

#For confidence level other than 95%, use conf.level argument.
#For 90% interval:
binomtestGC(~sex,data=m111survey,success="female",conf.level=0.90)

#For one-sided test, set alternative argument as desired:
binomtestGC(~sex,data=m111survey,p=0.50,
    success="female",alternative="greater")

#Summary data:
#In one sample, 40 successes in 100 trials.  Testing whether p = 0.45.
binomtestGC(x=40,n=100,p=0.45)
# }