我有一个名为corr_dat_cond1的数据帧，它有一个实验任务的试验。
> head(corr_dat_cond1)
participant search_difficulty key_resp.corr key_resp.rt target_position distractor1_colour distractor2_colour non_target_colour
1 1010 easy 1 1.1869998 right [0,0.5,1] [0,0.5,1] [0,0.59,0]
2 1010 difficult 1 1.2490001 down [0.82,0.31,0] [0.82,0,0.31] [0.82,0.31,0]
3 1010 easy 1 1.0100000 up [0,0.5,1] [0,0.59,0] [0,0.59,0]
4 1010 easy 1 0.8659999 down [0,0.5,1] [0,0.5,1] [0,0.59,0]
5 1010 no_search 1 0.8559999 right [-1,-1,-1] [-1,-1,-1] [-1,-1,-1]
6 1010 easy 1 0.6269999 right [0,0.5,1] [0,0.59,0] [0,0.59,0]
non_target_pos cue_uposition target_char non_target_char cue_time cue_colour cue_validity
1 [0,-0.328] up x = 1.4 Mismatch (Onset) cue FALSE
2 [0,0.328] left x = 1.0 Mismatch (Onset) cue FALSE
3 [0.328,0] down x = 1.1 Mismatch (Onset) cue FALSE
4 [0.328,0] right = x 1.4 Match (Color) cue FALSE
5 [-0.328,0] down = x 1.4 Mismatch (Onset) cue FALSE
6 [0,-0.328] right = x 1.4 Match (Color) cue TRUE
我的第二个数据帧是cond1_participant_meanrts，它为每个search_dffice级别中的每个参与者都有一个high_cutoff和low_cutoff。
> head(cond1_participant_meanrts)
# A tibble: 6 x 6
# Groups: participant [2]
participant search_difficulty mrt stdev low_cutoff high_cutoff
<dbl> <chr> <dbl> <dbl> <dbl> <dbl>
1 636 difficult 1.10 0.224 0.426 1.77
2 636 easy 0.986 0.270 0.177 1.79
3 636 no_search 0.909 0.298 0.0160 1.80
4 642 difficult 1.02 0.268 0.221 1.83
5 642 easy 0.887 0.237 0.175 1.60
6 642 no_search 0.809 0.225 0.135 1.48
如果key_resp.rt值大于cond1_participant_meanrts中相应的(基于参与者和search_dffice(high_cutoff值，或者如果key_resp.rt值小于cond1_particulant_meants中相应的low_cutoff，我希望删除corr_dat_cond1中的行。
有办法做到这一点吗？提前谢谢。
这就是您需要的吗？
corr_dat_cond1 %>%
dplyr::left_join(
cond1_participant_meanrts, by=c("participant", "search_difficulty")
) %>%
dplyr::filter(
key_resp.rt < high_cutoff | key_resp.rt > low_cutoff
)