为每个度量减去特定条件 [英] subtracting a specific condition for each measure

问题描述

我有一个如下所示的数据框，它一直持续到主题 22Beta 是依赖度量.

I have a data frame which looks like following and it continues up to subject 22 Beta is the dependent measure.

Subject ROI Block Condition Beta
1   motor1  1   nopred_noom -2.8653
1   motor1  1   pred_noom   -2.9126
1   motor1  1   nopred_om   -2.8688
1   motor1  1   pred_om -2.9098
1   motor1  1   null    -2.7717
1   motor1  2   nopred_noom -2.2382
1   motor1  2   pred_noom   -2.0583
1   motor1  2   nopred_om   -2.2207
1   motor1  2   pred_om -2.1928
1   motor1  2   null    -2.1166
1   motor1  3   nopred_noom -1.5992
1   motor1  3   pred_noom   -1.5493
1   motor1  3   nopred_om   -1.5230
1   motor1  3   pred_om -1.4851
1   motor1  3   null    -1.5624
2   motor1  1   nopred_noom -1.1354
2   motor1  1   pred_noom   -1.1614
2   motor1  1   nopred_om   -1.2779
2   motor1  1   pred_om -1.1234
2   motor1  1   null    -1.2203
2   motor1  2   nopred_noom -1.5728
2   motor1  2   pred_noom   -1.6614
2   motor1  2   nopred_om   -1.7076
2   motor1  2   pred_om -1.7702
2   motor1  2   null    -1.4170

有 5 个条件，但我想使用条件 null 作为基线，并希望从每个相应块和主题中的其他条件中减去它.

There are 5 conditions, but I want to use the condition null as the baseline and want to subtract it from other conditions in each corresponding block and subject.

所以我会从主题 1 块 1 中其他条件的 Beta 度量中减去主题 1 块 1 中的 Beta 值，块 1 但然后我想使用主题 1 块 2 中的 beta 值null"作为主题 1 中的度量、block2 等等.

so I would subtract Beta in subject 1, block 1, condition "null" from Beta measures in other conditions in subject1, block 1 but then I want to use beta value "null" from subject1, block2 for measures in subject 1, block2 and so on.

每 5 个条件出现一次空条件，我怀疑我需要使用循环，但我对 R 很陌生，我不知道如何做到这一点.

null condition occurs every 5 conditions and i suspect I need to use a loop but I am quite new to R and I am not sure how to do this.

感谢任何帮助！！！谢谢:)

any help is appreciated!!! thanks :)

推荐答案

以下是上述任务的基本 R 代码:

Here is base R code for the above task:

#-- split
dfs <- split(df, list(df$Block, df$Subject))
#-- apply
Beta0<-NULL
for (i in 1:length(dfs))
{Beta0 <- dfs[[i]]$Beta - dfs[[i]][dfs[[i]]$Condition=="null",]$Beta;
 dfs[[i]][,"Beta0"] <- Beta0}
#-- recombine
dfrc <- do.call(rbind, dfs)

df=原始数据框；dfs = 包含所有拆分子组的列表；dfrc = 新数据框，应重现上面为新列Beta0"显示的结果.

df= original data frame; dfs = a list comprising all the split subgroups; dfrc = new data frame that should reproduce the results displayed above for the new column "Beta0".

我发布这个是因为我有一个类似的数据集，其中一个块中条件null"的缺失值Beta".Plyr 产生了一条错误消息参数意味着不同的行数:x, 0"并且没有计算.然而，上面的代码为该块生成了 NA，但计算了所有其余的.

I posted this because I had a similar data set with - analagously - a missing value of "Beta" for the condition "null" in one block. Plyr produced an error message "arguments imply differing number of rows: x, 0" and di dnot compute. The above code, however, produced NAs for that block but computed all the rest.

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