logi.hist.plot: Plot logistic regression

In popbio: Construction and Analysis of Matrix Population Models

Plot logistic regression

Description

Plot combined graphs for logistic regressions

Usage

logi.hist.plot(
  independ,
  depend,
  logi.mod = 1,
  type = "dit",
  boxp = TRUE,
  rug = FALSE,
  ylabel = "Probability",
  ylabel2 = "Frequency",
  xlabel = "",
  mainlabel = "",
  las.h = 1,
  counts = FALSE,
  ...
)

Arguments

independ	explanatory variable
depend	dependent variable, typically a logical vector
logi.mod	type of fitting, 1 = logistic; 2 = "gaussian" logistic
type	type of representation, "dit" = dit plot; "hist" = histogram
boxp	TRUE = with box plots, FALSE = without
rug	TRUE = with rug plots, FALSE = without
ylabel	y-axis label
ylabel2	2nd y-axis label
xlabel	x-axix label
mainlabel	overall title for plot
las.h	orientation of axes labels (0 = vertical, 1 = horizontal
counts	add counts above histogram bars
...	additional options passed to logi.hist

Value

A logistic regression plot

Author(s)

M. de la Cruz Rot

References

de la Cruz Rot, M. 2005. Improving the Presentation of Results of Logistic Regression with R. ESA Bulletin 86:41-48. http://esapubs.org/bulletin/backissues/086-1/bulletinjan2005.htm

Examples

aq.trans$survived <- aq.trans$fate!="dead"
a <- subset(aq.trans, leaf<50 & stage!="recruit", c(leaf,survived))
logi.hist.plot(a$leaf,  a$survived,
  type="hist", boxp=FALSE, counts=TRUE, int=10,
  ylabel="Survival probability", ylabel2="Number of plants",
  xlab="Number of leaves")
b <- glm(survived ~ leaf, binomial, data=a)
summary(b)

popbio documentation built on May 29, 2024, 4:35 a.m.