I need to perform a meta-analysis of two studies with two variables of multiples levels of exposure
data1:
CA CO
0 405 457
1 101 108
2 22 16
3 6 5
4 0 1
data2:
CA CO
0 154 141
1 42 65
2 13 9
3 2 2
4 0 0
But I don't find the way to do it with metafor in R; anyone can help?
Thank you very much
Related
I made a frequency table with two variables in a data frame using this:
table(df$Variable1, df$Variable2)
The output was this:
1 2 3 4 5 D R
1 5000 21 39 2 10 0 112
2 1028 11 18 4 8 1 54
3 1501 6 12 2 3 0 68
4 355 2 4 0 0 0 23
5 421 4 4 0 0 0 49
Then I wanted to find the sum of the first two columns so I did this:
colSums(table(df$Variable1, df$Variable2))
The output was this:
1 2 3 4 5 D R
8305 44 77 8 21 1 306
Is there a way to find the sum of columns 1 and 2 from the colSums output above? What would the code be? Thanks in advance.
I was not so sure how to ask this question. i am trying to answer what is the average tone when an initiative is mentioned and additionally when a topic, and a goal( or achievement) are mentioned. My dataframe (df) has many mentions of 70 initiatives (rows). meaning my df has 500+ rows of data, but only 70 Initiatives.
My data looks like this
> tabmean
Initiative Topic Goals Achievements Tone
1 52 44 2 2 2
2 294 42 2 2 2
3 103 31 2 2 2
4 52 41 2 2 2
5 87 26 2 1 1
6 52 87 2 2 2
7 136 81 2 2 2
8 19 7 2 2 1
9 19 4 2 2 2
10 0 63 2 2 2
11 0 25 2 2 2
12 19 51 2 2 2
13 52 51 2 2 2
14 108 94 2 2 1
15 52 89 2 2 2
16 110 37 2 2 2
17 247 25 2 2 2
18 66 95 2 2 2
19 24 49 2 2 2
20 24 110 2 2 2
I want to find what is the mean or average Tone when an Initiative is mentioned. as well as what is the Tone when an Initiative, a Topic and a Goal are mentioned at the same time. The code options for Tone are : positive(coded: 1), neutral(2), negative (coded:3), and both positive and negative(4). Goals and Achievements are coded yes(1) and no(2).
I have used this code:
GoalMeanTone <- tabmean %>%
group_by(Initiative,Topic,Goals,Tone) %>%
summarize(averagetone = mean(Tone))
With Solution output :
GoalMeanTone
# A tibble: 454 x 5
# Groups: Initiative, Topic, Goals [424]
Initiative Topic Goals Tone averagetone
<chr> <chr> <chr> <chr> <dbl>
1 0 104 2 0 NA
2 0 105 2 0 NA
3 0 22 2 0 NA
4 0 25 2 0 NA
5 0 29 2 0 NA
6 0 30 2 1 NA
7 0 31 1 1 NA
8 0 42 1 0 NA
9 0 44 2 0 NA
10 0 44 NA 0 NA
# ... with 444 more rows
note that for Initiative Value 0 means "other initiative".
and I've also tried this code
library(plyr)
GoalMeanTone2 <- ddply( tabmean, .(Initiative), function(x) mean(tabmean$Tone) )
with solution output
> GoalMeanTone2
Initiative V1
1 0 NA
2 1 NA
3 101 NA
4 102 NA
5 103 NA
6 104 NA
7 105 NA
8 107 NA
9 108 NA
10 110 NA
Note that in both instances, I do not get an average for Tone but instead get NA's
I have removed the NAs in the df from the column "Tone" also have tried to remove all the other mission values in the df ( its only about 30 values that i deleted).
and I have also re-coded the values for Tone :
tabmean<-Meantable %>% mutate(Tone=recode(Tone,
`1`="1",
`2`="0",
`3`="-1",
`4`="2"))
I still cannot manage to get the average tone for an initiative. Maybe the solution is more obvious than i think, but have gotten stuck and have no idea how to proceed or solve this.
i'd be super grateful for a better code to get this. Thanks!
I'm not completely sure what you mean by 'the average tone when an initiative is mentioned', but let's say that you'd want to get the average tone for when initiative=1, you could try the following:
tabmean %>% filter(initiative==1) %>% summarise(avg_tone=mean(tone, na.rm=TRUE)
Note that (1) you have to add na.rm==TRUE to the summarise call if you have missing values in the column that you are summarizing, otherwise it will only produce NA's, and (2) check that the columns are of type numeric (you could check that with str(tabmean) and for example change tone to numeric with tabmean <- tabmean %>% mutate(tone=as.numeric(tone)).
I have a dataset of repeated measurements (hb) for patients (record_id) over several days. I have included an example below
record_id Day hb
1 0 122
1 1 90
1 2 71
1 3 71
2 0 139
2 1 130
2 2 119
2 3 106
3 0 89
3 1 126
3 2 127
3 3 110
4 0 90
4 1 86
4 2 82
4 3 78
5 0 118
5 1 108
5 2 95
5 3 94
I wish to find out the minimum value for "hb" for each patient:
#nadir Hb by patient
x1 <- aggregate(hb~record_id, data=df, FUN=function(df) c(min=min(df), count=length(df)))
summary(x1)
Would anyone be kind enough to show me how I could plot a histogram of these minimum values? Thank you very much for your time, Annemarie
I wonder how can I add more row numbers to points that are ploted on the linear regression residuals charts.Is there a way to add points number to the top 5% precents for example? or can I use a graphical position to mark specific rows?
I added a toy data frame and made a model (how can I display rows number to dots or chart's areas as I ploted in the regression diagnostics charts ( blue lines shapes) ?:
df <- read.table(text = "userid target birds wolfs
222 1 9 7
444 1 8 4
234 0 2 8
543 1 2 3
678 1 8 3
987 0 1 2
294 1 7 16
608 0 1 5
123 1 17 7
321 1 8 7
226 0 2 7
556 0 20 3
334 1 6 3
225 0 1 1
999 0 3 11
987 0 30 1 ",header = TRUE)
lm<-lm(target~birds+wolfs,data=df)
par(mfrow=c(2,2))
plot(lm)
Consider a data frame df with an extract from a web server access log, with two fields (sample below, duration is in msec and to simplify the example, let's ignore the date).
time,duration
18:17:26.552,8
18:17:26.632,10
18:17:26.681,12
18:17:26.733,4
18:17:26.778,5
18:17:26.832,5
18:17:26.889,4
18:17:26.931,3
18:17:26.991,3
18:17:27.040,5
18:17:27.157,4
18:17:27.209,14
18:17:27.249,4
18:17:27.303,4
18:17:27.356,13
18:17:27.408,13
18:17:27.450,3
18:17:27.506,13
18:17:27.546,3
18:17:27.616,4
18:17:27.664,4
18:17:27.718,3
18:17:27.796,10
18:17:27.856,3
18:17:27.909,3
18:17:27.974,3
18:17:28.029,3
qplot(time, duration, data=df); gives me a graph of the duration. I'd like to add, superimposed a line showing the number of requests for each minute. Ideally, this line would have a single data point per minute, at the :30sec point. If that's too complicated, an acceptable alternative is to have a step line, with the same value (the count of request) during a minute.
One way is to trunc(df$time, units=c("mins")), then calculate the count of request per minute into a new column then graph it.
I'm asking if there is, perhaps, a more direct way to accomplish the above. Thanks.
Following may be helpful. Create a data frame with steps and plot:
time duration sec sec2 diffsec2 step30s steps
1 18:17:26.552 8 26.552 552 0 0 0
2 18:17:26.632 10 26.632 632 80 1 1
3 18:17:26.681 12 26.681 681 49 0 0
4 18:17:26.733 4 26.733 733 52 1 1
5 18:17:26.778 5 26.778 778 45 0 0
6 18:17:26.832 5 26.832 832 54 1 1
7 18:17:26.889 4 26.889 889 57 1 2
8 18:17:26.931 3 26.931 931 42 0 0
9 18:17:26.991 3 26.991 991 60 1 1
10 18:17:27.040 5 27.040 040 -951 0 0
11 18:17:27.157 4 27.157 157 117 1 1
12 18:17:27.209 14 27.209 209 52 1 2
13 18:17:27.249 4 27.249 249 40 0 0
14 18:17:27.303 4 27.303 303 54 1 1
15 18:17:27.356 13 27.356 356 53 1 2
16 18:17:27.408 13 27.408 408 52 1 3
17 18:17:27.450 3 27.450 450 42 0 0
18 18:17:27.506 13 27.506 506 56 1 1
19 18:17:27.546 3 27.546 546 40 0 0
20 18:17:27.616 4 27.616 616 70 1 1
21 18:17:27.664 4 27.664 664 48 0 0
22 18:17:27.718 3 27.718 718 54 1 1
23 18:17:27.796 10 27.796 796 78 1 2
24 18:17:27.856 3 27.856 856 60 1 3
25 18:17:27.909 3 27.909 909 53 1 4
26 18:17:27.974 3 27.974 974 65 1 5
27 18:17:28.029 3 28.029 029 -945 0 0
>
> ggplot(ddf)+geom_point(aes(x=time, y=duration))+geom_line(aes(x=time, y=steps, group=1),color='red')