визуализация линейной смешанной модели в R - PullRequest
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визуализация линейной смешанной модели в R

0 голосов
/ 18 апреля 2020

Я использую линейную смешанную модель для набора данных. Траектория развития двух групп, оцененная в 3 момента времени по ряду различных показателей. Переменными предиктора являются возраст и материнское образование. Я использую пакеты nlme и ggplot2. Вот моя последняя модель (GM_RAW - зависимая переменная) 

Model_5<-lme(GM_RAW~timepoint*Group+age+Maternal_Education, data=dat, 
random=~timepoint|ID,method="ML", na.action=na.omit,control=list(opt="optim"))
summary(Model_5)

Я составил отдельные траектории на основе необработанных данных, но я хочу добавить информацию из прогнозируемых линий из модели для моих 2 групп. Я пробовал различные предложения, опубликованные по переполнению стека, но ни одно из них, похоже, не работает 

dat$gmpred<-predict(Model_5)

GrossMotor<-ggplot(dat,aes(x=as.numeric(timepoint),y=GM_RAW,colour=Group))+
geom_point()+ geom_line(aes(group=ID))

GrossMotor + geom_line(data=dat, aes(y=gmpred))

Я хочу показать перехват и наклон для моих 2 групп на конечном графике

некоторые примеры данных 

"","ID","timepoint","Maternal_Education","age","Group","GM_RAW"
"1",3012,"5 months",NA,188,"Typical Group",10
"2",3089,"5 months",NA,182,"Typical Group",9
"3",3012,"10 months",NA,328,"Typical Group",13
"4",3004,"5 months","Tertiary postgraduate",163,"Typical Group",6
"5",3008,"5 months","Tertiary postgraduate",171,"Typical Group",4
"6",3023,"5 months","Tertiary postgraduate",170,"Typical Group",8
"7",3063,"5 months","Tertiary postgraduate",181,"Typical Group",10
"8",3071,"5 months","Tertiary postgraduate",151,"Typical Group",8
"9",3074,"5 months","Tertiary postgraduate",183,"Typical Group",9
"10",3075,"5 months","Tertiary postgraduate",165,"Typical Group",9
"11",3087,"5 months","Tertiary postgraduate",172,"Typical Group",6
"12",3104,"5 months","Tertiary postgraduate",180,"Typical Group",7
"13",3115,"5 months","Tertiary postgraduate",199,"Typical Group",8
"14",3142,"5 months","Tertiary postgraduate",201,"Typical Group",9
"15",3161,"5 months","Tertiary postgraduate",189,"Typical Group",7
"16",3162,"5 months","Tertiary postgraduate",201,"Typical Group",8
"17",4002,"5 months","Tertiary postgraduate",202,"NF1",8
"18",4024,"5 months","Tertiary postgraduate",167,"NF1",8
"19",3004,"10 months","Tertiary postgraduate",315,"Typical Group",9
"20",3008,"10 months","Tertiary postgraduate",341,"Typical Group",9
"21",3023,"10 months","Tertiary postgraduate",358,"Typical Group",14
"22",3063,"10 months","Tertiary postgraduate",293,"Typical Group",17
"23",3071,"10 months","Tertiary postgraduate",302,"Typical Group",12
"24",3074,"10 months","Tertiary postgraduate",333,"Typical Group",12
"25",3075,"10 months","Tertiary postgraduate",318,"Typical Group",11
"26",3078,"10 months","Tertiary postgraduate",304,"Typical Group",9
"27",3087,"10 months","Tertiary postgraduate",335,"Typical Group",13
"28",3104,"10 months","Tertiary postgraduate",294,"Typical Group",10
"29",3115,"10 months","Tertiary postgraduate",305,"Typical Group",11
"30",3142,"10 months","Tertiary postgraduate",327,"Typical Group",11
"31",3161,"10 months","Tertiary postgraduate",328,"Typical Group",12
"32",3162,"10 months","Tertiary postgraduate",333,"Typical Group",10
"33",4002,"10 months","Tertiary postgraduate",335,"NF1",11
"34",4009,"10 months","Tertiary postgraduate",320,"NF1",11
"35",4024,"10 months","Tertiary postgraduate",351,"NF1",13
"36",3004,"14 months","Tertiary postgraduate",438,"Typical Group",21
"37",3008,"14 months","Tertiary postgraduate",460,"Typical Group",9
"38",3023,"14 months","Tertiary postgraduate",471,"Typical Group",18
"39",3063,"14 months","Tertiary postgraduate",445,"Typical Group",20

1 Ответ

0 голосов
/ 18 апреля 2020

Я думаю, проблема в том, как вы строите свою модель. На основании ваших данных мне пришлось убрать несколько ковариат, чтобы модель работала. Кроме того, если вы включите случайный эффект для «ID», у вас будут разные перехваты для каждого ID, и, таким образом, для каждого момента времени у вас будет несколько значений y в столбце прогноза. ggplot связывает их, но, конечно, выглядит совершенно криво.

Таким образом, я удалил идентификатор как случайный эффект, и вы увидите, что сюжет работает. 

library(tidyverse)


foo <- foo %>% mutate(timepoint = str_replace(timepoint, " months", ""))

Model_5 <- nlme::lme(GM_RAW ~ Group,
  data = foo,
  random = ~ 1 | timepoint, method = "ML", na.action = na.omit
)

foo$gmpred <- predict(Model_5)

ggplot(foo, aes(x = as.numeric(timepoint), y = GM_RAW, colour = Group)) +
  geom_point() +
  geom_line(aes(group = ID)) +
  geom_line(aes(y = gmpred, group = Group, linetype = Group), color = "black")

Если вам действительно нужно добавить ID как случайный эффект, вам нужно изменить переменную группировки для geom_line, я использую interaction()

Model_5 <- nlme::lme(GM_RAW ~ Group,
  data = foo,
  random = ~ timepoint | ID, method = "ML", na.action = na.omit
)

foo$gmpred <- predict(Model_5)

ggplot(foo, aes(x = as.numeric(timepoint), y = GM_RAW, colour = Group)) +
  geom_point() +
  geom_line(aes(group = ID)) +
  geom_line(aes(y = gmpred, group = interaction(Group,ID), linetype = Group), color = "black")

Создано в 2020-04-18 с помощью представительного пакета (v0.3.0)

данные 

foo <- readr::read_csv(",ID,timepoint,Maternal_Education,age,Group,GM_RAW
1,3012,5 months,NA,188,Typical Group,10
2,3089,5 months,NA,182,Typical Group,9
3,3012,10 months,NA,328,Typical Group,13
4,3004,5 months,Tertiary postgraduate,163,Typical Group,6
5,3008,5 months,Tertiary postgraduate,171,Typical Group,4
6,3023,5 months,Tertiary postgraduate,170,Typical Group,8
7,3063,5 months,Tertiary postgraduate,181,Typical Group,10
8,3071,5 months,Tertiary postgraduate,151,Typical Group,8
9,3074,5 months,Tertiary postgraduate,183,Typical Group,9
10,3075,5 months,Tertiary postgraduate,165,Typical Group,9
11,3087,5 months,Tertiary postgraduate,172,Typical Group,6
12,3104,5 months,Tertiary postgraduate,180,Typical Group,7
13,3115,5 months,Tertiary postgraduate,199,Typical Group,8
14,3142,5 months,Tertiary postgraduate,201,Typical Group,9
15,3161,5 months,Tertiary postgraduate,189,Typical Group,7
16,3162,5 months,Tertiary postgraduate,201,Typical Group,8
17,4002,5 months,Tertiary postgraduate,202,NF1,8
18,4024,5 months,Tertiary postgraduate,167,NF1,8
19,3004,10 months,Tertiary postgraduate,315,Typical Group,9
20,3008,10 months,Tertiary postgraduate,341,Typical Group,9
21,3023,10 months,Tertiary postgraduate,358,Typical Group,14
22,3063,10 months,Tertiary postgraduate,293,Typical Group,17
23,3071,10 months,Tertiary postgraduate,302,Typical Group,12
24,3074,10 months,Tertiary postgraduate,333,Typical Group,12
25,3075,10 months,Tertiary postgraduate,318,Typical Group,11
26,3078,10 months,Tertiary postgraduate,304,Typical Group,9
27,3087,10 months,Tertiary postgraduate,335,Typical Group,13
28,3104,10 months,Tertiary postgraduate,294,Typical Group,10
29,3115,10 months,Tertiary postgraduate,305,Typical Group,11
30,3142,10 months,Tertiary postgraduate,327,Typical Group,11
31,3161,10 months,Tertiary postgraduate,328,Typical Group,12
32,3162,10 months,Tertiary postgraduate,333,Typical Group,10
33,4002,10 months,Tertiary postgraduate,335,NF1,11
34,4009,10 months,Tertiary postgraduate,320,NF1,11
35,4024,10 months,Tertiary postgraduate,351,NF1,13
36,3004,14 months,Tertiary postgraduate,438,Typical Group,21
37,3008,14 months,Tertiary postgraduate,460,Typical Group,9
38,3023,14 months,Tertiary postgraduate,471,Typical Group,18
39,3063,14 months,Tertiary postgraduate,445,Typical Group,20")
#> Warning: Missing column names filled in: 'X1' [1]
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