ci_wald: Wald Confidence Intervals

In jeksterslabds/jeksterslabRds: Jekster's Lab Data Science and Statistics

Description

Generates symmetric confidence intervals using the Wald method.

Usage

ci_wald(est, se)

Arguments

est	Parameter estimate.
se	Standard error.

Value

Returns a vector with the following elements:

se

Standard error.

z

z statistic.

p

p-value.

sig_001

Logical. Tests if p < 0.001.

sig_01

Logical. Tests if p < 0.01.

sig_05

Logical. Tests if p < 0.05.

ll_001

Lower limit. Alpha 0.001.

ll_01

Lower limit. Alpha 0.01.

ll_05

Lower limit. Alpha 0.05.

ul_05

Upper limit. Alpha 0.05.

ul_01

Upper limit. Alpha 0.01.

ul_001

Upper limit. Alpha 0.001.

zero_hit_001

Logical. Tests if ll_001 < 0 < ul_001.

zero_hit_01

Logical. Tests if ll_01 < 0 < ul_01.

zero_hit_05

Logical. Tests if ll_05 < 0 < ul_05.

ci_width_001

ll_001 - ul_001.

ci_width_01

ll_01 - ul_01.

ci_width_05

ll_05 - ul_05.

ci_shape_001

Confidence interval shape. Alpha 0.001.

ci_shape_01

Confidence interval shape. Alpha 0.01.

ci_shape_05

Confidence interval shape. Alpha 0.05.

Note that se, z, p, and sig are based on the normal theory. Confidence limits for ci_wald are based on the normal theory. Ajustments for asymmetry for ci_bc and ci_bca are made in the confidence limits.

See Also

Other confidence interval functions: ci_bca(), ci_bc(), ci_quantile()

Examples

ci_wald(est = 0.26^(1 / 2), se = 0.25)

jeksterslabds/jeksterslabRds documentation built on July 16, 2020, 3:41 p.m.