Inserting NA's in case there are not enough observations

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Ayala Allon

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Nov 26, 2014, 9:08:07 AM11/26/14

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Hi,

I have the following data frame (this is only the head of the data frame). The ID column is subject (I have more subjects in the data frame, not only subject #99). I want to calculate the mean "rt" by "subject" and "condition" only for observations that have z.score (in absolute values) smaller than 1.

> head(b)

subject rt ac condition z.score

1 99 1253 1 200_9 1.20862682

2 99 1895 1 102_2 2.95813507

3 99 1049 1 68_1 1.16862102

4 99 1732 1 68_9 2.94415384

5 99 765 1 34_9 -0.63991180

7 99 1016 1 68_2 -0.03191493

I know I can to do it using tapply or dcast after subsetting the data:

b1 <- subset(b, abs(z.score) < 1)

b2 <- dcast(b1, subject~condition, mean, value.var = "rt")

and then I get:

> b2

subject 34_1 34_2 34_9 68_1 68_2 68_9 102_1 102_2 102_9 200_1 200_2

1 99 1028.5714 957.5385 861.6818 837.0000 969.7222 856.4000 912.5556 977.7273 858.7800 1006.0000 1015.3684

2 5203 957.8889 815.2500 845.7750 933.0000 893.0000 883.0435 926.0000 879.2778 813.7308 804.2857 803.8125

3 5205 1456.3333 1008.4286 850.7170 1142.4444 910.4706 998.4667 935.2500 980.9167 897.4681 1040.8000 838.7917

4 5306 1022.2000 940.5882 904.6562 1525.0000 1216.0000 929.5167 955.8571 981.7500 902.8913 997.6000 924.6818

5 5307 1396.1250 1217.1111 1044.4038 1055.5000 1115.6000 980.5833 1003.5714 1482.8571 941.4490 1091.5556 1125.2143

6 5308 659.8571 904.2857 966.7755 960.9091 1048.6000 904.5082 836.2000 1753.6667 926.0400 870.2222 1066.6667

200_9

1 913.2449

2 843.7200

3 819.9710

4 883.4583

5 989.4918

6 930.7500

In the example above for b1 each of the subjects had observations that met the subset demands.

However, it can be that for a certain subject I won't have observations after I subset. In this case I want to get NA in b2 for that subject in the specific condition in which he doesn't have observations that meet the subset demands. Does anyone have an idea for a way to do that?

Any help will be greatly appreciated.

Best,

Ayala

Jonathan Rosenblatt

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Nov 26, 2014, 3:59:08 PM11/26/14

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I would definitely begin by using the dplyr package to do it, and then check if the package behaves like you want.

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