PIKAL Petr
2015-Feb-09 11:01 UTC
[R] suggestion for optimal plotting to show significant differences
Hallo Richard. I tried your suggestion but it seems to be no better than simple ggplot. Let me extend the example a bit to 8 items which is more realistic. item<-rep(letters[1:8], each=18) day<-rep((0:5)*100, 24) set<-rep(rep(1:3, each=6), 8) test<-data.frame(item, day, set) set.seed(111) test$value<-(test$day/100+1)+rnorm(144) test$value<-test$value+(as.numeric(test$item)*1.3) Value is increasing during time (day) for each tested subject (item), each item is measured 3 times (set) each day. Here is some graph p<-ggplot(test, aes(x=day, y=value, colour=item)) p+geom_point()+stat_smooth(method="lm", formula= y~poly(x,2)) I can do lm or aov, however I am not sure about proper formula. fit<-lm(value~day, data=test) summary(fit) # this shows that value is increasing with day fit<-lm(value~day/item, data=test) summary(fit) # this suggests that value is decreasing with day (which is wrong) fit<-lm(value~day*item, data=test) summary(fit) # and this tells me that value is increasing with day and items have different intercepts but the same rate of growth (I hope I got it right). I do not have your book available but I went through help pages. Your interaction graph is not much better than ggplot. I can do interaction2wt(value ~ item * day, data=test) which probably is closer to actual problem. The basic problem is that increase of value with days is in fact not linear and actually it can increase in the beginning and then stagnate or it can stagnate in beginning and then increase. I am not aware of any way how to compare time behaviour of different items in such situations if I cannot state some common formula in which case I would use probably nlme. Thank for your insight, I try to go through it more deeply. Best regards Petr> -----Original Message----- > From: Richard M. Heiberger [mailto:rmh at temple.edu] > Sent: Friday, February 06, 2015 6:14 PM > To: PIKAL Petr > Cc: r-help at r-project.org > Subject: Re: [R] suggestion for optimal plotting to show significant > differences > > I would try one of these illustrations for starts. > interaction2wt (two-way tables) is designed to be used with aov() for > testing. > interaction2wt shows all main effects and all two-way interactions for > many factors. > > > > test <- > structure(list(item = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, > 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, > 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("A", "B"), class > "factor"), day = c(0L, 100L, 200L, 300L, 400L, 500L, 0L, 100L, 200L, > 300L, 400L, 500L, 0L, 100L, 200L, 300L, 400L, 500L, 0L, 100L, 200L, > 300L, 400L, 500L, 0L, 100L, 200L, 300L, 400L, 500L, 0L, 100L, 200L, > 300L, 400L, 500L), set = c(1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, > 2L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, > 2L, 3L, 3L, 3L, 3L, 3L, 3L), value = c(1.08163365169503, > 2.61998412608805, 3.07820466606394, 4.44993419381934, 5.29163171545805, > 6.29155990999293, -0.123163011367676, 2.07767236834003, > 2.32537052874901, 3.09372794501084, 6.65273721166635, 5.92304962329131, > 1.50504697705548, 2.66253728086866, 2.63420157418685, 2.78195098580416, > 6.47578642973288, 5.89587443775143, 0.848864231485078, > 1.27549677119713, 2.19573089053609, 2.45659926134292, 5.15424403414103, > 5.4813151140983, 1.25731482647214, 2.09662105167973, 1.75954023316977, > 4.81624002288939, 4.65029189325307, 6.39946904227214, > 0.944996929887344, 1.74667265331284, 2.42956264345558, > 5.17852980415141, 3.5453435965834, 6.9011238437191)), .Names > c("item", "day", "set", "value"), row.names = c(NA, -36L), class > "data.frame") > > > > library(HH) > > test$set <- factor(test$set) > test$day <- factor(test$day) > test$item <- factor(test$item) > > interaction2wt(value ~ item * day * set, data=test) > > test$item.day <- interaction(test$item, test$day) > position(test$item.day) <- outer(c(-10,10), > as.numeric(levels(test$day)), `+`) > > xyplot(value ~ as.position(item.day) | set, groups=item, > data=test, horizontal=FALSE, pch=c(17,16), > xlab="day", > scales=list( > x=list( > alternating=1, > at=levels(test$day), ## placement of tick labels and marks > tck=1)), > key=list( > text=list(c("A","B"), col=c("blue","red")), > points=list(pch=c(17, 16), col=c("blue","red")), > space="top", columns=2, border=TRUE), > layout=c(3,1)) > > > ## see also the examples in > demo(package="HH", bwplot.examples) > > On Fri, Feb 6, 2015 at 6:09 AM, PIKAL Petr <petr.pikal at precheza.cz> > wrote: > > Dear all > > > > I would like to ask for your opinion about possible graphical > representation of such data. > > > >> dput(test) > > structure(list(item = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, > > 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, > > 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("A", "B"), class > > > "factor"), day = c(0L, 100L, 200L, 300L, 400L, 500L, 0L, 100L, 200L, > > 300L, 400L, 500L, 0L, 100L, 200L, 300L, 400L, 500L, 0L, 100L, 200L, > > 300L, 400L, 500L, 0L, 100L, 200L, 300L, 400L, 500L, 0L, 100L, 200L, > > 300L, 400L, 500L), set = c(1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, > 2L, > > 2L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, > > 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L), value = c(1.08163365169503, > > 2.61998412608805, 3.07820466606394, 4.44993419381934, > > 5.29163171545805, 6.29155990999293, -0.123163011367676, > > 2.07767236834003, 2.32537052874901, 3.09372794501084, > > 6.65273721166635, 5.92304962329131, 1.50504697705548, > > 2.66253728086866, 2.63420157418685, 2.78195098580416, > > 6.47578642973288, 5.89587443775143, 0.848864231485078, > > 1.27549677119713, 2.19573089053609, 2.45659926134292, > > 5.15424403414103, 5.4813151140983, 1.25731482647214, > 2.09662105167973, > > 1.75954023316977, 4.81624002288939, 4.65029189325307, > > 6.39946904227214, 0.944996929887344, 1.74667265331284, > > 2.42956264345558, 5.17852980415141, 3.5453435965834, > > 6.9011238437191)), .Names = c("item", "day", "set", "value"), > > row.names = c(NA, -36L), class = "data.frame") > >> > > > > One option I came with is > > > > library(ggplot2) > > p<-ggplot(test, aes(x=day, y=value, colour=item)) > > p+geom_point()+stat_smooth(method="lm", formula= y~poly(x,2)) > > > > but - > > I have more items (around 5-10), and I want to show if the difference > between items is or is not significant. The actual development of value > with day is usually not linear nor growing steadily and actually I > cannot usually evaluate some analytical equation for my data to compare > equation parameters. > > > > I thought about boxplots, but there is not many repetitions and > actually 5+ boxplots can be quite messy. > > > > I can plot only mean for each set and item but in that case I lose > information if the difference is or is not significant. > > > > I appreciate any suggestion. > > > > Best regards > > Petr > > > > > > > > > > > > > > > > > > ________________________________ > > Tento e-mail a jak?koliv k n?mu p?ipojen? dokumenty jsou d?v?rn? a > jsou ur?eny pouze jeho adres?t?m. > > Jestli?e jste obdr?el(a) tento e-mail omylem, informujte laskav? > neprodlen? jeho odes?latele. Obsah tohoto emailu i s p??lohami a jeho > kopie vyma?te ze sv?ho syst?mu. > > Nejste-li zam??len?m adres?tem tohoto emailu, nejste opr?vn?ni tento > email jakkoliv u??vat, roz?i?ovat, kop?rovat ?i zve?ej?ovat. > > Odes?latel e-mailu neodpov?d? za eventu?ln? ?kodu zp?sobenou > modifikacemi ?i zpo?d?n?m p?enosu e-mailu. > > > > V p??pad?, ?e je tento e-mail sou??st? obchodn?ho jedn?n?: > > - vyhrazuje si odes?latel pr?vo ukon?it kdykoliv jedn?n? o uzav?en? > smlouvy, a to z jak?hokoliv d?vodu i bez uveden? d?vodu. > > - a obsahuje-li nab?dku, je adres?t opr?vn?n nab?dku bezodkladn? > p?ijmout; Odes?latel tohoto e-mailu (nab?dky) vylu?uje p?ijet? nab?dky > ze strany p??jemce s dodatkem ?i odchylkou. > > - trv? odes?latel na tom, ?e p??slu?n? smlouva je uzav?ena teprve > v?slovn?m dosa?en?m shody na v?ech jej?ch n?le?itostech. > > - odes?latel tohoto emailu informuje, ?e nen? opr?vn?n uzav?rat za > spole?nost ??dn? smlouvy s v?jimkou p??pad?, kdy k tomu byl p?semn? > zmocn?n nebo p?semn? pov??en a takov? pov??en? nebo pln? moc byly > adres?tovi tohoto emailu p??padn? osob?, kterou adres?t zastupuje, > p?edlo?eny nebo jejich existence je adres?tovi ?i osob? j?m zastoupen? > zn?m?. > > > > This e-mail and any documents attached to it may be confidential and > are intended only for its intended recipients. > > If you received this e-mail by mistake, please immediately inform its > sender. 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Jestli?e jste obdr?el(a) tento e-mail omylem, informujte laskav? neprodlen? jeho odes?latele. Obsah tohoto emailu i s p??lohami a jeho kopie vyma?te ze sv?ho syst?mu. Nejste-li zam??len?m adres?tem tohoto emailu, nejste opr?vn?ni tento email jakkoliv u??vat, roz?i?ovat, kop?rovat ?i zve?ej?ovat. Odes?latel e-mailu neodpov?d? za eventu?ln? ?kodu zp?sobenou modifikacemi ?i zpo?d?n?m p?enosu e-mailu. V p??pad?, ?e je tento e-mail sou??st? obchodn?ho jedn?n?: - vyhrazuje si odes?latel pr?vo ukon?it kdykoliv jedn?n? o uzav?en? smlouvy, a to z jak?hokoliv d?vodu i bez uveden? d?vodu. - a obsahuje-li nab?dku, je adres?t opr?vn?n nab?dku bezodkladn? p?ijmout; Odes?latel tohoto e-mailu (nab?dky) vylu?uje p?ijet? nab?dky ze strany p??jemce s dodatkem ?i odchylkou. - trv? odes?latel na tom, ?e p??slu?n? smlouva je uzav?ena teprve v?slovn?m dosa?en?m shody na v?ech jej?ch n?le?itostech. - odes?latel tohoto emailu informuje, ?e nen? opr?vn?n uzav?rat za spole?nost ??dn? smlouvy s v?jimkou p??pad?, kdy k tomu byl p?semn? zmocn?n nebo p?semn? pov??en a takov? pov??en? nebo pln? moc byly adres?tovi tohoto emailu p??padn? osob?, kterou adres?t zastupuje, p?edlo?eny nebo jejich existence je adres?tovi ?i osob? j?m zastoupen? zn?m?. This e-mail and any documents attached to it may be confidential and are intended only for its intended recipients. If you received this e-mail by mistake, please immediately inform its sender. Delete the contents of this e-mail with all attachments and its copies from your system. If you are not the intended recipient of this e-mail, you are not authorized to use, disseminate, copy or disclose this e-mail in any manner. The sender of this e-mail shall not be liable for any possible damage caused by modifications of the e-mail or by delay with transfer of the email. In case that this e-mail forms part of business dealings: - the sender reserves the right to end negotiations about entering into a contract in any time, for any reason, and without stating any reasoning. - if the e-mail contains an offer, the recipient is entitled to immediately accept such offer; The sender of this e-mail (offer) excludes any acceptance of the offer on the part of the recipient containing any amendment or variation. - the sender insists on that the respective contract is concluded only upon an express mutual agreement on all its aspects. - the sender of this e-mail informs that he/she is not authorized to enter into any contracts on behalf of the company except for cases in which he/she is expressly authorized to do so in writing, and such authorization or power of attorney is submitted to the recipient or the person represented by the recipient, or the existence of such authorization is known to the recipient of the person represented by the recipient.
Richard M. Heiberger
2015-Feb-11 21:53 UTC
[R] suggestion for optimal plotting to show significant differences
Petr,
My first attempt is to use the simple=TRUE argument to interaction2wt.
Then the bwplots in the item|item panel show the behavior of value over day
for each item. You get a plot similar to this panel with the growth curve plots
from nlme, for example,
bwplot(value ~ day | item, data=test, horizontal=FALSE)
I am treating set as a replication and each box is cumulated over the
three sets.
My analysis question is about day. You have it as numeric. My
inclination would
be to make day factor. Then you could model the interaction of day and item.
Rich
On Mon, Feb 9, 2015 at 6:01 AM, PIKAL Petr <petr.pikal at precheza.cz>
wrote:> Hallo Richard.
>
> I tried your suggestion but it seems to be no better than simple ggplot.
Let me extend the example a bit to 8 items which is more realistic.
>
> item<-rep(letters[1:8], each=18)
> day<-rep((0:5)*100, 24)
> set<-rep(rep(1:3, each=6), 8)
> test<-data.frame(item, day, set)
> set.seed(111)
> test$value<-(test$day/100+1)+rnorm(144)
> test$value<-test$value+(as.numeric(test$item)*1.3)
>
> Value is increasing during time (day) for each tested subject (item), each
item is measured 3 times (set) each day.
>
> Here is some graph
> p<-ggplot(test, aes(x=day, y=value, colour=item))
> p+geom_point()+stat_smooth(method="lm", formula= y~poly(x,2))
>
> I can do lm or aov, however I am not sure about proper formula.
>
> fit<-lm(value~day, data=test)
> summary(fit)
> # this shows that value is increasing with day
>
> fit<-lm(value~day/item, data=test)
> summary(fit)
> # this suggests that value is decreasing with day (which is wrong)
>
> fit<-lm(value~day*item, data=test)
> summary(fit)
> # and this tells me that value is increasing with day and items have
different intercepts but the same rate of growth (I hope I got it right).
>
> I do not have your book available but I went through help pages.
>
> Your interaction graph is not much better than ggplot.
> I can do
>
> interaction2wt(value ~ item * day, data=test)
>
> which probably is closer to actual problem.
>
> The basic problem is that increase of value with days is in fact not linear
and actually it can increase in the beginning and then stagnate or it can
stagnate in beginning and then increase. I am not aware of any way how to
compare time behaviour of different items in such situations if I cannot state
some common formula in which case I would use probably nlme.
>
> Thank for your insight, I try to go through it more deeply.
>
> Best regards
> Petr
>
>
>> -----Original Message-----
>> From: Richard M. Heiberger [mailto:rmh at temple.edu]
>> Sent: Friday, February 06, 2015 6:14 PM
>> To: PIKAL Petr
>> Cc: r-help at r-project.org
>> Subject: Re: [R] suggestion for optimal plotting to show significant
>> differences
>>
>> I would try one of these illustrations for starts.
>> interaction2wt (two-way tables) is designed to be used with aov() for
>> testing.
>> interaction2wt shows all main effects and all two-way interactions for
>> many factors.
>>
>>
>>
>> test <-
>> structure(list(item = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
>> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
>> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("A",
"B"), class >> "factor"), day = c(0L, 100L, 200L,
300L, 400L, 500L, 0L, 100L, 200L,
>> 300L, 400L, 500L, 0L, 100L, 200L, 300L, 400L, 500L, 0L, 100L, 200L,
>> 300L, 400L, 500L, 0L, 100L, 200L, 300L, 400L, 500L, 0L, 100L, 200L,
>> 300L, 400L, 500L), set = c(1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L,
>> 2L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L,
>> 2L, 3L, 3L, 3L, 3L, 3L, 3L), value = c(1.08163365169503,
>> 2.61998412608805, 3.07820466606394, 4.44993419381934, 5.29163171545805,
>> 6.29155990999293, -0.123163011367676, 2.07767236834003,
>> 2.32537052874901, 3.09372794501084, 6.65273721166635, 5.92304962329131,
>> 1.50504697705548, 2.66253728086866, 2.63420157418685, 2.78195098580416,
>> 6.47578642973288, 5.89587443775143, 0.848864231485078,
>> 1.27549677119713, 2.19573089053609, 2.45659926134292, 5.15424403414103,
>> 5.4813151140983, 1.25731482647214, 2.09662105167973, 1.75954023316977,
>> 4.81624002288939, 4.65029189325307, 6.39946904227214,
>> 0.944996929887344, 1.74667265331284, 2.42956264345558,
>> 5.17852980415141, 3.5453435965834, 6.9011238437191)), .Names >>
c("item", "day", "set", "value"),
row.names = c(NA, -36L), class >> "data.frame")
>>
>>
>>
>> library(HH)
>>
>> test$set <- factor(test$set)
>> test$day <- factor(test$day)
>> test$item <- factor(test$item)
>>
>> interaction2wt(value ~ item * day * set, data=test)
>>
>> test$item.day <- interaction(test$item, test$day)
>> position(test$item.day) <- outer(c(-10,10),
>> as.numeric(levels(test$day)), `+`)
>>
>> xyplot(value ~ as.position(item.day) | set, groups=item,
>> data=test, horizontal=FALSE, pch=c(17,16),
>> xlab="day",
>> scales=list(
>> x=list(
>> alternating=1,
>> at=levels(test$day), ## placement of tick labels and marks
>> tck=1)),
>> key=list(
>> text=list(c("A","B"),
col=c("blue","red")),
>> points=list(pch=c(17, 16),
col=c("blue","red")),
>> space="top", columns=2, border=TRUE),
>> layout=c(3,1))
>>
>>
>> ## see also the examples in
>> demo(package="HH", bwplot.examples)
>>
>> On Fri, Feb 6, 2015 at 6:09 AM, PIKAL Petr <petr.pikal at
precheza.cz>
>> wrote:
>> > Dear all
>> >
>> > I would like to ask for your opinion about possible graphical
>> representation of such data.
>> >
>> >> dput(test)
>> > structure(list(item = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L,
>> > 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L,
>> > 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("A",
"B"), class
>> >> > "factor"), day = c(0L, 100L, 200L, 300L, 400L,
500L, 0L, 100L, 200L,
>> > 300L, 400L, 500L, 0L, 100L, 200L, 300L, 400L, 500L, 0L, 100L,
200L,
>> > 300L, 400L, 500L, 0L, 100L, 200L, 300L, 400L, 500L, 0L, 100L,
200L,
>> > 300L, 400L, 500L), set = c(1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L,
>> 2L,
>> > 2L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L,
2L,
>> > 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L), value = c(1.08163365169503,
>> > 2.61998412608805, 3.07820466606394, 4.44993419381934,
>> > 5.29163171545805, 6.29155990999293, -0.123163011367676,
>> > 2.07767236834003, 2.32537052874901, 3.09372794501084,
>> > 6.65273721166635, 5.92304962329131, 1.50504697705548,
>> > 2.66253728086866, 2.63420157418685, 2.78195098580416,
>> > 6.47578642973288, 5.89587443775143, 0.848864231485078,
>> > 1.27549677119713, 2.19573089053609, 2.45659926134292,
>> > 5.15424403414103, 5.4813151140983, 1.25731482647214,
>> 2.09662105167973,
>> > 1.75954023316977, 4.81624002288939, 4.65029189325307,
>> > 6.39946904227214, 0.944996929887344, 1.74667265331284,
>> > 2.42956264345558, 5.17852980415141, 3.5453435965834,
>> > 6.9011238437191)), .Names = c("item", "day",
"set", "value"),
>> > row.names = c(NA, -36L), class = "data.frame")
>> >>
>> >
>> > One option I came with is
>> >
>> > library(ggplot2)
>> > p<-ggplot(test, aes(x=day, y=value, colour=item))
>> > p+geom_point()+stat_smooth(method="lm", formula=
y~poly(x,2))
>> >
>> > but -
>> > I have more items (around 5-10), and I want to show if the
difference
>> between items is or is not significant. The actual development of value
>> with day is usually not linear nor growing steadily and actually I
>> cannot usually evaluate some analytical equation for my data to compare
>> equation parameters.
>> >
>> > I thought about boxplots, but there is not many repetitions and
>> actually 5+ boxplots can be quite messy.
>> >
>> > I can plot only mean for each set and item but in that case I lose
>> information if the difference is or is not significant.
>> >
>> > I appreciate any suggestion.
>> >
>> > Best regards
>> > Petr
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> > ________________________________
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> ________________________________
> Tento e-mail a jak?koliv k n?mu p?ipojen? dokumenty jsou d?v?rn? a jsou
ur?eny pouze jeho adres?t?m.
> Jestli?e jste obdr?el(a) tento e-mail omylem, informujte laskav? neprodlen?
jeho odes?latele. Obsah tohoto emailu i s p??lohami a jeho kopie vyma?te ze
sv?ho syst?mu.
> Nejste-li zam??len?m adres?tem tohoto emailu, nejste opr?vn?ni tento email
jakkoliv u??vat, roz?i?ovat, kop?rovat ?i zve?ej?ovat.
> Odes?latel e-mailu neodpov?d? za eventu?ln? ?kodu zp?sobenou modifikacemi
?i zpo?d?n?m p?enosu e-mailu.
>
> V p??pad?, ?e je tento e-mail sou??st? obchodn?ho jedn?n?:
> - vyhrazuje si odes?latel pr?vo ukon?it kdykoliv jedn?n? o uzav?en?
smlouvy, a to z jak?hokoliv d?vodu i bez uveden? d?vodu.
> - a obsahuje-li nab?dku, je adres?t opr?vn?n nab?dku bezodkladn? p?ijmout;
Odes?latel tohoto e-mailu (nab?dky) vylu?uje p?ijet? nab?dky ze strany p??jemce
s dodatkem ?i odchylkou.
> - trv? odes?latel na tom, ?e p??slu?n? smlouva je uzav?ena teprve v?slovn?m
dosa?en?m shody na v?ech jej?ch n?le?itostech.
> - odes?latel tohoto emailu informuje, ?e nen? opr?vn?n uzav?rat za
spole?nost ??dn? smlouvy s v?jimkou p??pad?, kdy k tomu byl p?semn? zmocn?n nebo
p?semn? pov??en a takov? pov??en? nebo pln? moc byly adres?tovi tohoto emailu
p??padn? osob?, kterou adres?t zastupuje, p?edlo?eny nebo jejich existence je
adres?tovi ?i osob? j?m zastoupen? zn?m?.
>
> This e-mail and any documents attached to it may be confidential and are
intended only for its intended recipients.
> If you received this e-mail by mistake, please immediately inform its
sender. Delete the contents of this e-mail with all attachments and its copies
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> If you are not the intended recipient of this e-mail, you are not
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> The sender of this e-mail shall not be liable for any possible damage
caused by modifications of the e-mail or by delay with transfer of the email.
>
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recipient, or the existence of such authorization is known to the recipient of
the person represented by the recipient.
PIKAL Petr
2015-Feb-12 14:48 UTC
[R] suggestion for optimal plotting to show significant differences
Hi Rich> -----Original Message----- > From: Richard M. Heiberger [mailto:rmh at temple.edu] > Sent: Wednesday, February 11, 2015 10:53 PM > To: PIKAL Petr > Cc: r-help at r-project.org > Subject: Re: [R] suggestion for optimal plotting to show significant > differences > > Petr, > > My first attempt is to use the simple=TRUE argument to interaction2wt. > > Then the bwplots in the item|item panel show the behavior of value over > day for each item. You get a plot similar to this panel with the > growth curve plots from nlme, for example, > bwplot(value ~ day | item, data=test, horizontal=FALSE) I am > treating set as a replication and each box is cumulated over the three > sets.Yes, that is the point - set is actually replication of result.> > My analysis question is about day. You have it as numeric. My > inclination would be to make day factor. Then you could model the > interaction of day and item.Hm. I hoped I can do fit<-lm(value~day*item, data=test) summary(fit) in which case I can compare differences in intercepts and/or slopes for each item. However I am rather lost in aov test$dayf <- factor(test$day) fit1 <- aov(value~item+dayf, data=test) summary(fit) fit2 <- aov(value~item/dayf, data=test) summary(fit) and fit3 <- aov(value~item*dayf, data=test) summary(fit) which gives bascally the same result as fit2> anova(fit1, fit2)Analysis of Variance Table Model 1: value ~ item + dayf Model 2: value ~ item/dayf Res.Df RSS Df Sum of Sq F Pr(>F) 1 131 160.59 2 96 128.60 35 31.993 0.6824 0.8993 TukeyHSD(fit1, which="item") TukeyHSD(fit2, which="item") Both models seems to give quite similar results and I am not sure what actually differs in those models. I believe that model2 tests each item within particular day (but I am not sure about it). However this discussion is probably deviating more to the statistics issue than to R itself. I just thought that somebody helps me with a method for comparison of item performance in case that relation of value to day is not simple linear (as in my example) and cannot be expressed by some formula (like examples in nlme). So far the best options are either your bwplot or my ggplots. p<-ggplot(test, aes(x=day, y=value, colour=item)) p+geom_point()+stat_smooth(method="lm", formula= y~poly(x,2)) p<-ggplot(test, aes(x=dayf, y=value, colour=item)) p+geom_boxplot() p<-ggplot(test, aes(x=item, y=value)) p+geom_boxplot()+facet_wrap(~day) Thank you for your suggestions which directed me to interaction plots which I was not aware of. Best regards Petr> > Rich > > On Mon, Feb 9, 2015 at 6:01 AM, PIKAL Petr <petr.pikal at precheza.cz> > wrote: > > Hallo Richard. > > > > I tried your suggestion but it seems to be no better than simple > ggplot. Let me extend the example a bit to 8 items which is more > realistic. > > > > item<-rep(letters[1:8], each=18) > > day<-rep((0:5)*100, 24) > > set<-rep(rep(1:3, each=6), 8) > > test<-data.frame(item, day, set) > > set.seed(111) > > test$value<-(test$day/100+1)+rnorm(144) > > test$value<-test$value+(as.numeric(test$item)*1.3) > > > > Value is increasing during time (day) for each tested subject (item), > each item is measured 3 times (set) each day. > > > > Here is some graph > > p<-ggplot(test, aes(x=day, y=value, colour=item)) > > p+geom_point()+stat_smooth(method="lm", formula= y~poly(x,2)) > > > > I can do lm or aov, however I am not sure about proper formula. > > > > fit<-lm(value~day, data=test) > > summary(fit) > > # this shows that value is increasing with day > > > > fit<-lm(value~day/item, data=test) > > summary(fit) > > # this suggests that value is decreasing with day (which is wrong) > > > > fit<-lm(value~day*item, data=test) > > summary(fit) > > # and this tells me that value is increasing with day and items have > different intercepts but the same rate of growth (I hope I got it > right). > > > > I do not have your book available but I went through help pages. > > > > Your interaction graph is not much better than ggplot. > > I can do > > > > interaction2wt(value ~ item * day, data=test) > > > > which probably is closer to actual problem. > > > > The basic problem is that increase of value with days is in fact not > linear and actually it can increase in the beginning and then stagnate > or it can stagnate in beginning and then increase. I am not aware of > any way how to compare time behaviour of different items in such > situations if I cannot state some common formula in which case I would > use probably nlme. > > > > Thank for your insight, I try to go through it more deeply. > > > > Best regards > > Petr > > > > > >> -----Original Message----- > >> From: Richard M. Heiberger [mailto:rmh at temple.edu] > >> Sent: Friday, February 06, 2015 6:14 PM > >> To: PIKAL Petr > >> Cc: r-help at r-project.org > >> Subject: Re: [R] suggestion for optimal plotting to show significant > >> differences > >> > >> I would try one of these illustrations for starts. > >> interaction2wt (two-way tables) is designed to be used with aov() > for > >> testing. > >> interaction2wt shows all main effects and all two-way interactions > >> for many factors. > >> > >> > >> > >> test <- > >> structure(list(item = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, > 1L, > >> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, > >> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("A", "B"), class > >> = "factor"), day = c(0L, 100L, 200L, 300L, 400L, 500L, 0L, 100L, > >> 200L, 300L, 400L, 500L, 0L, 100L, 200L, 300L, 400L, 500L, 0L, 100L, > >> 200L, 300L, 400L, 500L, 0L, 100L, 200L, 300L, 400L, 500L, 0L, 100L, > >> 200L, 300L, 400L, 500L), set = c(1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, > >> 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, > >> 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L), value = c(1.08163365169503, > >> 2.61998412608805, 3.07820466606394, 4.44993419381934, > >> 5.29163171545805, 6.29155990999293, -0.123163011367676, > >> 2.07767236834003, 2.32537052874901, 3.09372794501084, > >> 6.65273721166635, 5.92304962329131, 1.50504697705548, > >> 2.66253728086866, 2.63420157418685, 2.78195098580416, > >> 6.47578642973288, 5.89587443775143, 0.848864231485078, > >> 1.27549677119713, 2.19573089053609, 2.45659926134292, > >> 5.15424403414103, 5.4813151140983, 1.25731482647214, > >> 2.09662105167973, 1.75954023316977, 4.81624002288939, > >> 4.65029189325307, 6.39946904227214, 0.944996929887344, > >> 1.74667265331284, 2.42956264345558, 5.17852980415141, > >> 3.5453435965834, 6.9011238437191)), .Names = c("item", "day", "set", > >> "value"), row.names = c(NA, -36L), class > >> "data.frame") > >> > >> > >> > >> library(HH) > >> > >> test$set <- factor(test$set) > >> test$day <- factor(test$day) > >> test$item <- factor(test$item) > >> > >> interaction2wt(value ~ item * day * set, data=test) > >> > >> test$item.day <- interaction(test$item, test$day) > >> position(test$item.day) <- outer(c(-10,10), > >> as.numeric(levels(test$day)), `+`) > >> > >> xyplot(value ~ as.position(item.day) | set, groups=item, > >> data=test, horizontal=FALSE, pch=c(17,16), > >> xlab="day", > >> scales=list( > >> x=list( > >> alternating=1, > >> at=levels(test$day), ## placement of tick labels and > marks > >> tck=1)), > >> key=list( > >> text=list(c("A","B"), col=c("blue","red")), > >> points=list(pch=c(17, 16), col=c("blue","red")), > >> space="top", columns=2, border=TRUE), > >> layout=c(3,1)) > >> > >> > >> ## see also the examples in > >> demo(package="HH", bwplot.examples) > >> > >> On Fri, Feb 6, 2015 at 6:09 AM, PIKAL Petr <petr.pikal at precheza.cz> > >> wrote: > >> > Dear all > >> > > >> > I would like to ask for your opinion about possible graphical > >> representation of such data. > >> > > >> >> dput(test) > >> > structure(list(item = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, > >> > 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, > 2L, > >> > 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("A", "B"), > >> > class > >> > >> > "factor"), day = c(0L, 100L, 200L, 300L, 400L, 500L, 0L, 100L, > >> > 200L, 300L, 400L, 500L, 0L, 100L, 200L, 300L, 400L, 500L, 0L, > 100L, > >> > 200L, 300L, 400L, 500L, 0L, 100L, 200L, 300L, 400L, 500L, 0L, > 100L, > >> > 200L, 300L, 400L, 500L), set = c(1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, > >> > 2L, 2L, > >> 2L, > >> > 2L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, > 2L, > >> > 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L), value = c(1.08163365169503, > >> > 2.61998412608805, 3.07820466606394, 4.44993419381934, > >> > 5.29163171545805, 6.29155990999293, -0.123163011367676, > >> > 2.07767236834003, 2.32537052874901, 3.09372794501084, > >> > 6.65273721166635, 5.92304962329131, 1.50504697705548, > >> > 2.66253728086866, 2.63420157418685, 2.78195098580416, > >> > 6.47578642973288, 5.89587443775143, 0.848864231485078, > >> > 1.27549677119713, 2.19573089053609, 2.45659926134292, > >> > 5.15424403414103, 5.4813151140983, 1.25731482647214, > >> 2.09662105167973, > >> > 1.75954023316977, 4.81624002288939, 4.65029189325307, > >> > 6.39946904227214, 0.944996929887344, 1.74667265331284, > >> > 2.42956264345558, 5.17852980415141, 3.5453435965834, > >> > 6.9011238437191)), .Names = c("item", "day", "set", "value"), > >> > row.names = c(NA, -36L), class = "data.frame") > >> >> > >> > > >> > One option I came with is > >> > > >> > library(ggplot2) > >> > p<-ggplot(test, aes(x=day, y=value, colour=item)) > >> > p+geom_point()+stat_smooth(method="lm", formula= y~poly(x,2)) > >> > > >> > but - > >> > I have more items (around 5-10), and I want to show if the > >> > difference > >> between items is or is not significant. The actual development of > >> value with day is usually not linear nor growing steadily and > >> actually I cannot usually evaluate some analytical equation for my > >> data to compare equation parameters. > >> > > >> > I thought about boxplots, but there is not many repetitions and > >> actually 5+ boxplots can be quite messy. > >> > > >> > I can plot only mean for each set and item but in that case I lose > >> information if the difference is or is not significant. > >> > > >> > I appreciate any suggestion. > >> > > >> > Best regards > >> > Petr > >> >________________________________ Tento e-mail a jak?koliv k n?mu p?ipojen? dokumenty jsou d?v?rn? a jsou ur?eny pouze jeho adres?t?m. Jestli?e jste obdr?el(a) tento e-mail omylem, informujte laskav? neprodlen? jeho odes?latele. Obsah tohoto emailu i s p??lohami a jeho kopie vyma?te ze sv?ho syst?mu. Nejste-li zam??len?m adres?tem tohoto emailu, nejste opr?vn?ni tento email jakkoliv u??vat, roz?i?ovat, kop?rovat ?i zve?ej?ovat. Odes?latel e-mailu neodpov?d? za eventu?ln? ?kodu zp?sobenou modifikacemi ?i zpo?d?n?m p?enosu e-mailu. V p??pad?, ?e je tento e-mail sou??st? obchodn?ho jedn?n?: - vyhrazuje si odes?latel pr?vo ukon?it kdykoliv jedn?n? o uzav?en? smlouvy, a to z jak?hokoliv d?vodu i bez uveden? d?vodu. - a obsahuje-li nab?dku, je adres?t opr?vn?n nab?dku bezodkladn? p?ijmout; Odes?latel tohoto e-mailu (nab?dky) vylu?uje p?ijet? nab?dky ze strany p??jemce s dodatkem ?i odchylkou. - trv? odes?latel na tom, ?e p??slu?n? smlouva je uzav?ena teprve v?slovn?m dosa?en?m shody na v?ech jej?ch n?le?itostech. - odes?latel tohoto emailu informuje, ?e nen? opr?vn?n uzav?rat za spole?nost ??dn? smlouvy s v?jimkou p??pad?, kdy k tomu byl p?semn? zmocn?n nebo p?semn? pov??en a takov? pov??en? nebo pln? moc byly adres?tovi tohoto emailu p??padn? osob?, kterou adres?t zastupuje, p?edlo?eny nebo jejich existence je adres?tovi ?i osob? j?m zastoupen? zn?m?. 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In case that this e-mail forms part of business dealings: - the sender reserves the right to end negotiations about entering into a contract in any time, for any reason, and without stating any reasoning. - if the e-mail contains an offer, the recipient is entitled to immediately accept such offer; The sender of this e-mail (offer) excludes any acceptance of the offer on the part of the recipient containing any amendment or variation. - the sender insists on that the respective contract is concluded only upon an express mutual agreement on all its aspects. - the sender of this e-mail informs that he/she is not authorized to enter into any contracts on behalf of the company except for cases in which he/she is expressly authorized to do so in writing, and such authorization or power of attorney is submitted to the recipient or the person represented by the recipient, or the existence of such authorization is known to the recipient of the person represented by the recipient.