L_regress: Likelihood Support for Regression

In likelihoodR: Likelihood Analyses for Common Statistical Tests

Likelihood Support for Regression

Description

This function calculates the supports for different regression fits from 2 vectors of data. Models include linear, quadratic and cubic (given sufficient data). A plot is included showing linear (black), quadratic (red) and cubic (blue dashed) lines. P values for the model fits are also given.

Usage

L_regress(y, x, verb=TRUE)

Arguments

y	a numeric vector the same length as x.
x	a numeric vector.
verb	show output, default = TRUE.

Value

$S.LNc - corrected support for linear versus null model.

$S.LN - uncorrected support for linear versus null model.

$S.QLc - corrected support for quadratic versus linear model.

$S.QL - uncorrected support for quadratic versus linear model.

S.QCc = support for quadratic versus cubic model.

$N - sample size.

$p.vals - p values for 3 fits.

References

Cahusac, P.M.B. (2020) Evidence-Based Statistics, Wiley, ISBN : 978-1119549802

Royall, R. M. (1997). Statistical evidence: A likelihood paradigm. London: Chapman & Hall, ISBN : 978-0412044113

Edwards, A.W.F. (1992) Likelihood, Johns Hopkins Press, ISBN : 978-0801844430

Examples

# for women's world record times for 1500m event example, p 108
years <- c(0.0,	7.1,	8.9,	8.9,	10.1,	12.8,	17.0,	19.1,
25.0, 28.7, 29.7,	29.9,	35.3, 39.8,	40.2,	41.9,	42.1,	44.0,
44.9, 45.0,	45.1, 45.1,	48.9,	52.9,	53.0,	66.1,	87.9)
time <- c(5.30,	5.12,	5.03,	4.79,	4.75,	4.70,	4.63,	4.63,
4.62, 4.59,	4.50,	4.50,	4.32,   4.29,	4.26,	4.21,	4.18,
4.16,	4.12, 4.11,	4.09,	4.02,	3.93,	3.92,	3.87,	3.84,	3.83)

m=L_regress(time, years)
m

likelihoodR documentation built on Sept. 14, 2023, 9:08 a.m.