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我尝试汇总来自信号检测实验的数据来计算命中率、误报率等。

   Code Cond bf1 bf2 bf3 bf4 bm1 bm2 bm3 bm4
BAX-011    3  CR  FA HIT  FA  FR  CR  FA  FA

我的变量 bf1 到 bm3 是具有级别的因素(hit,fa,cr,fr)。

我想计算命中数，fa's ...for each参与者（行），但使用变量子集（bf-items and bm-items）。执行此操作的最简单方法是什么？

最后应该是这样的：

   Code Cond bf1 bf2 bf3 bf4 bm1 bm2 bm3 bm4 bf_hits bm_hits bf_fa ...
BAX-011    3  CR  FA HIT  FA  FR  CR  FA  FA       1       0     2 ...
4

2 回答 2

1

如果我正确理解了您的问题，您可能只需要从“reshape2”包中melt进行探索。dcast使用@zx8754 的示例数据，尝试以下操作：

library(reshape2)

### Make the data into a "long" format
dfL <- melt(df, id.vars=c("Code", "Cond"))

### Split the existing "variable" column. 
### Here's one way to do that.
dfL <- cbind(dfL, setNames(
  do.call(rbind.data.frame, strsplit(
    as.character(dfL$variable), "(?=\\d)", perl=TRUE)), 
  c("var", "time")))

### This is what the data now look like.
head(dfL)
#      Code Cond variable value var time
# 1 BAX-011    3      bf1    CR  bf    1
# 2 BAX-012    3      bf1    CR  bf    1
# 3 BAX-013    3      bf1    CR  bf    1
# 4 BAX-011    3      bf2    FA  bf    2
# 5 BAX-012    3      bf2    FA  bf    2
# 6 BAX-013    3      bf2   HIT  bf    2

### Use `dcast` to aggregate the data. 
### The default function is "length" which is what you're looking for.
dcast(dfL, Code + Cond ~ var + value, value.var="value")
# Aggregation function missing: defaulting to length
#      Code Cond bf_CR bf_FA bf_HIT bm_CR bm_FA bm_FR bm_HIT
# 1 BAX-011    3     1     2      1     1     2     1      0
# 2 BAX-012    3     1     2      1     0     2     1      1
# 3 BAX-013    3     1     1      2     0     2     1      1

从那里，您可以随时merge或cbind相关栏目一起获得完整的data.frame.

更新

为了避免被视为“reshape2”的粉丝，这里有一个基本的 R 方法。我希望它也能说明我为什么在这种情况下选择“reshape2”路线：

X <- grep("^bf|^bm", names(df))
df[X] <- lapply(df[X], as.character)
dfL <- cbind(dfL, setNames(
  do.call(rbind.data.frame, strsplit(
    as.character(dfL$ind), "(?=\\d)", perl=TRUE)),
  c("var", "time")))
dfL$X <- paste(dfL$var, dfL$values, sep ="_")
dfA <- aggregate(values ~ Code + Cond + X, dfL, length)
reshape(dfA, direction = "wide", idvar=c("Code", "Cond"), timevar="X")
于 2013-11-12T16:47:22.657 回答
0

尝试这个：

#dummy data
df <- read.table(text="
Code Cond bf1 bf2 bf3 bf4 bm1 bm2 bm3 bm4
BAX-011    3  CR  FA HIT  FA  FR  CR  FA  FA
BAX-012    3  CR  FA HIT  FA  FR  HIT  FA  FA
BAX-013    3  CR  HIT HIT  FA  FR  HIT  FA  FA
", header=TRUE)

#count HITs per bf bm
df$bf_hit <- rowSums(df[,colnames(df)[grepl("bf",colnames(df))]]=="HIT")
df$bm_hit <- rowSums(df[,colnames(df)[grepl("bm",colnames(df))]]=="HIT")

#output
df
#Code Cond bf1 bf2 bf3 bf4 bm1 bm2 bm3 bm4 bf_hit bm_hit
#1 BAX-011    3  CR  FA HIT  FA  FR  CR  FA  FA      1      0
#2 BAX-012    3  CR  FA HIT  FA  FR HIT  FA  FA      1      1
#3 BAX-013    3  CR HIT HIT  FA  FR HIT  FA  FA      2      1
于 2013-11-12T14:15:55.243 回答