Commit dec5c48aa7469c601ff9f757ba1ffebc2a8bacda - effects

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DESCRIPTION less more

0	0	Package: effects
1		Version: 2.0-4
2		Date: 2009/03/26
	1	Version: 2.0-5
	2	Date: 2009/04/09
3	3	Title: Effect Displays for Linear, Generalized Linear,
4	4	Multinomial-Logit, and Proportional-Odds Logit Models
5	5	Author: John Fox <jfox@mcmaster.ca> and Jangman Hong. We are grateful

16	16	URL: http://www.r-project.org, http://socserv.socsci.mcmaster.ca/jfox/
17	17	Repository: CRAN
18	18	Repository/R-Forge/Project: effects
19		Repository/R-Forge/Revision: 27
20		Publication/Date: 2009-03-27 02:25:06
21		Packaged: Wed Apr 1 05:14:22 2009; rforge
22		Date/Publication: 2009-04-01 17:01:40
	19	Repository/R-Forge/Revision: 30
	20	Publication/Date: 2009-04-09 15:04:11
	21	Packaged: Mon Apr 13 17:50:14 2009; rforge
	22	Date/Publication: 2009-04-15 07:34:13

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R/plot-summary-print-methods.R less more

0	0	# plot, summary, and print methods for effects package
1	1	# John Fox and Jangman Hong
2		# last modified 19 March 2009 by J. Fox
	2	# last modified 9 April 2009 by J. Fox
3	3
4	4
5	5	summary.eff <- function(object, type=c("response", "link"), ...){

37	37
38	38	print.summary.eff <- function(x, ...){
39	39	cat(x$header)
40		print(x$effect)
	40	print(x$effect, ...)
41	41	if (!is.null(x$lower)){
42	42	cat(x$lower.header)
43		print(x$lower)
	43	print(x$lower, ...)
44	44	cat(x$upper.header)
45		print(x$upper)
	45	print(x$upper, ...)
46	46	}
47	47	if (!is.null(x$thresholds)){
48	48	cat("\nThresholds:\n")
49		print(x$thresholds)
	49	print(x$thresholds, ...)
50	50	}
51	51	if (!is.null(x$warning)) cat(x$warning)
52	52	invisible(x)

59	59	table <- array(x$fit,
60	60	dim=sapply(x$variables, function(x) length(x$levels)),
61	61	dimnames=lapply(x$variables, function(x) x$levels))
62		print(table)
	62	print(table, ...)
63	63	if (x$discrepancy > 1e-3) cat(paste("\nWarning: There is an average discrepancy of",
64	64	round(x$discrepancy, 3),
65	65	"percent \n in the 'safe' predictions for effect", x$term, '\n'))

426	426	else {x$logit[y.categories==y.lev[i]]},
427	427	dim=sapply(x$variables, function(x) length(x$levels)),
428	428	dimnames=lapply(x$variables, function(x) x$levels))
429		print(table)
	429	print(table, ...)
430	430	}
431	431	if (x$discrepancy > 0.1) cat(paste("\nWarning: There is an average discrepancy of",
432	432	round(x$discrepancy, 2),

457	457	else {object$logit[y.categories==y.lev[i]]},
458	458	dim=sapply(object$variables, function(x) length(x$levels)),
459	459	dimnames=lapply(object$variables, function(x) x$levels))
460		print(table)
	460	print(table, ...)
461	461	}
462	462	if (is.null(object$confidence.level)) return(invisible(NULL))
463	463	for (i in 1:length(y.lev)){

467	467	table <- array(table[y.categories==y.lev[i]],
468	468	dim=sapply(object$variables, function(x) length(x$levels)),
469	469	dimnames=lapply(object$variables, function(x) x$levels))
470		print(table)
	470	print(table, ...)
471	471	}
472	472	for (i in 1:length(y.lev)){
473	473	cat(paste("\n", 'Upper', object$confidence.level*100, 'Percent Confidence Limits for'

476	476	table <- array(table[y.categories==y.lev[i]],
477	477	dim=sapply(object$variables, function(x) length(x$levels)),
478	478	dimnames=lapply(object$variables, function(x) x$levels))
479		print(table)
	479	print(table, ...)
480	480	}
481	481	if (object$discrepancy > 0.1) cat(paste("\nWarning: There is an average discrepancy of",
482	482	round(object$discrepancy, 2),

784	784	table <- array(x$fit,
785	785	dim=sapply(x$variables, function(x) length(x$levels)),
786	786	dimnames=lapply(x$variables, function(x) x$levels))
787		print(table)
	787	print(table, ...)
788	788	cat("\nThresholds:\n")
789		print(x$thresholds)
	789	print(x$thresholds, ...)
790	790	if (x$discrepancy > 0.1) cat(paste("\nWarning: There is an average discrepancy of",
791	791	round(x$discrepancy, 3),
792	792	"percent \n in the 'safe' predictions for effect", x$term, '\n'))

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inst/CHANGES less more

90	90	o Added Titanic and Wells data sets.
91	91
92	92	o Small changes.
	93
	94	Version 2.0-5
	95
	96	o Added examples for Titanic, BEPS, and WVS data sets.
	97
	98	o Arguments ... (e.g., digits) passed through in print() methods.

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man/BEPS.Rd less more

31	31
32	32	\examples{
33	33	summary(BEPS)
	34
	35	require(splines) # for bs()
	36	beps <- multinom(vote ~ age + gender + economic.cond.national + economic.cond.household
	37	+ Blair + Hague + Kennedy + bs(Europe, 3)*political.knowledge, data=BEPS)
	38	europe.knowledge <- effect("bs(Europe, 3)*political.knowledge", beps,
	39	xlevels=list(Europe=seq(1, 11, length=50), political.knowledge=0:3),
	40	given.values=c(gendermale=0.5))
	41
	42	plot(europe.knowledge)
	43
	44	plot(europe.knowledge, style="stacked", colors=c("blue", "red", "orange"), rug=FALSE)
34	45	}
35	46
36	47	\keyword{datasets}

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man/Titanic.Rd less more

37	37	New York: Springer.
38	38	}
39	39	\examples{
40		summary(Titanic)
	40	summary(Titanic)
	41
	42	titanic <- glm(survived ~ (passengerClass + sex + age)^2, data=Titanic, family=binomial)
	43
	44	titanic.all <- allEffects(titanic, typical=median,
	45	given.values=c(passengerClass2nd=1/3, passengerClass3rd=1/3, sexmale=0.5))
	46
	47	plot(titanic.all, ticks=list(at=c(.01, .05, seq(.1, .9, by=.2), .95, .99)), ask=FALSE)
	48
	49	plot(effect("passengerClasssexage", titanic, xlevels=list(age=0:65)),
	50	ticks=list(at=c(.001, .005, .01, .05, seq(.1, .9, by=.2), .95, .99, .995)))
41	51	}
42	52	\keyword{datasets}

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man/WVS.Rd less more

27	27
28	28	\examples{
29	29	summary(WVS)
	30
	31	require(splines) # for bs()
	32	wvs <- polr(poverty ~ gender + country*(religion + degree + bs(age, 4)), data=WVS)
	33
	34	plot(effect("country*bs(age,4)", wvs, xlevels=list(age=18:83),
	35	given.values=c(gendermale=0.5)), rug=FALSE)
	36
	37	plot(effect("country*bs(age,4)", wvs, xlevels=list(age=18:83),
	38	given.values=c(gendermale=0.5)), rug=FALSE, style="stacked")
	39
	40	plot(effect("country*bs(age,4)", wvs, xlevels=list(age=18:83),
	41	given.values=c(gendermale=0.5), latent=TRUE), rug=FALSE)
30	42	}
31	43
32	44	\keyword{datasets}

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man/effect.Rd less more

145	145	corresponding to the high-order terms of the model.
146	146	}
147	147
	148	\section{Warning}{
	149	The \code{effect} function handles factors and covariates differently, and becomes confused if one is changed to the other
	150	in a model formula. Consequently, formulas that include calls to \code{as.factor}, \code{factor}, or \code{numeric}
	151	(as, e.g., in \code{as.factor(income)}) will cause errors. Instead, create the modified variables outside of the model
	152	formula (e.g., \code{fincome <- as.factor(income)}) and use these in the model formula.
	153	}
	154
148	155	\references{
149	156	Fox, J. (1987)
150	157	Effect displays for generalized linear models.