proptest_num | R Documentation |
Computes all results for test on proportion using either stats::binom.test()
, or
a normal approximation without continuity correction.
Either named parameters can be given or an arglist
with the following parameters:
x
number of successes
n
sample size (default: sd(x)
)
pi0
true value of the proportion (default: 0.5
)
alternative
a string specifying the alternative hypothesis (default: "two.sided"
), otherwise "greater"
or "less"
can be used
alpha
significance level (default: 0.05
)
binom2norm
can the binomial distribution be approximated by a normal distribution? (default: NA
= use binom2norm
function)
proptest_num(..., arglist = NULL)
prop_binomtest_num(..., arglist = NULL)
nbinomtest(..., arglist = NULL)
... |
named input parameters |
arglist |
list: named input parameters, if given |
The results of proptest_num
may differ from stats::binom.test()
. proptest_num
is designed to return results
when you compute a binomial test by hand. For example, for computing the test statistic the approximation t_n \approx N(0; 1)
is used if n>n.tapprox
. The p.value
is computed by stats::binom.test and may not be reliable, for Details see Note!
A list with the input parameters and the following:
X
distribution of the random sampling function
Statistic
distribution of the test statistics
statistic
test value
critical
critical value(s)
criticalx
critical value(s) in x range
acceptance0
acceptance interval for H0
acceptance0x
acceptance interval for H0 in x range
accept1
is H1 accepted?
p.value
p value for test (note: the p-value may not be reliable see Notes!)
alphaexact
exact significance level
stderr
standard error of the proportion used as denominator
The computation of a p-value for non-symmetric distribution is not well defined, see https://stats.stackexchange.com/questions/140107/p-value-in-a-two-tail-test-with-asymmetric-null-distribution.
n <- 100
x <- sum(runif(n)<0.4)
proptest_num(x=x, n=n)
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