simple subgroup analysis

[eberk]

I am trying to get simple stat #s for subgroups of data

my answers are coming up as NaN and NA

this is one example:
mean(hw1.1$blame_attribution[hw1.1$pid_root==1], na.rm=TRUE)

when i calc for the whole group, blame_attribution, i am getting the correct numbers

please help

[andresrcs]

Hi!

To help us help you, could you please prepare a reproducible example (reprex) illustrating your issue? Please have a look at this guide, to see how to create one:

FAQ: How to do a minimal reproducible example ( reprex ) for beginners

A minimal reproducible example consists of the following items: A minimal dataset, necessary to reproduce the issue The minimal runnable code necessary to reproduce the issue, which can be run on the given dataset, and including the necessary information on the used packages. Let's quickly go over each one of these with examples: Minimal Dataset (Sample Data) You need to provide a data frame that is small enough to be (reasonably) pasted on a post, but big enough to reproduce your issue. Let's say, as an example, that you are working with the iris data frame head(iris) #> Sepal.Length Sepal.Width Petal.Length Petal.Width Species #> 1 5.1 3.5 1.4 0.…

[eberk]

ï..pid_root slider_undoc vote2020 income education st_postal sex system_justification blame_attribution restriction
1 1 5 1 8 6 MO 0 3.714286 0.000 1.2
2 1 5 1 9 5 NJ 0 4.428571 0.125 2.0
3 2 20 2 11 5 MA 1 3.000000 0.125 1.8
4 1 50 4 1 1 LA 0 4.285714 0.125 4.0
5 3 11 4 8 4 NC 0 3.857143 0.000 1.8
6 3 20 2 11 3 AZ 0 4.571429 0.000 1.4

#Democrat identifiers
mean(hw1.1$blame_attribution[hw1.1$pid_root==2], na.rm=TRUE)
sd(hw1.1$blame_attribution[hw1.1$pid_root==2], na.rm=TRUE)
median(hw1.1$blame_attribution[hw1.1$pid_root==2], na.rm=TRUE)
IQR(hw1.1$blame_attribution[hw1.1$pid_root==2], na.rm=TRUE)

[andresrcs]

I can't reproduce your issue with the data you are providing (see example below), please provide a proper reproducible example for your issue as explained in the link I gave you before.

hw1.1 <- data.frame(stringsAsFactors=FALSE,
               pid_root = c(1, 1, 2, 1, 3, 3),
           slider_undoc = c(5, 5, 20, 50, 11, 20),
               vote2020 = c(1, 1, 2, 4, 4, 2),
                 income = c(8, 9, 11, 1, 8, 11),
              education = c(6, 5, 5, 1, 4, 3),
              st_postal = c("MO", "NJ", "MA", "LA", "NC", "AZ"),
                    sex = c(0, 0, 1, 0, 0, 0),
   system_justification = c(3.714286, 4.428571, 3, 4.285714, 3.857143, 4.571429),
      blame_attribution = c(0, 0.125, 0.125, 0.125, 0, 0),
            restriction = c(1.2, 2, 1.8, 4, 1.8, 1.4)
)

mean(hw1.1$blame_attribution[hw1.1$pid_root==2], na.rm=TRUE)
#> [1] 0.125
sd(hw1.1$blame_attribution[hw1.1$pid_root==2], na.rm=TRUE) # Not possible to calculate with just one value
#> [1] NA
median(hw1.1$blame_attribution[hw1.1$pid_root==2], na.rm=TRUE)
#> [1] 0.125
IQR(hw1.1$blame_attribution[hw1.1$pid_root==2], na.rm=TRUE)
#> [1] 0

^{Created on 2019-10-28 by the reprex package (v0.3.0.9000)}