R语言双条件随机游走模拟器问题：条件交替逻辑修复求助

问题根源 #

原代码循环逻辑错误：先完整执行条件1的100次试次，将结果写入Trial=1~100；接着执行条件2的100次试次，同样写入Trial=1~100，导致条件2的数据完全覆盖条件1，最终所有试次都显示条件2的配置。

需求是试次按**1→条件1、2→条件2、3→条件1、4→条件2...**的交替逻辑运行。

修复后的代码 #

#Set a seed
set.seed(2024)

#Variable declaration-------------
nConds <- 2     #Number of conditions
stim <- c("R", "L")       #Stimulus labels
pi <- c(.75, .65)         #Probability of step (+1) for random walk; 1-pi will be the probability of stepping -1
diff <- c("Easy", "Hard")  #Difficulty label for the condition
mean_a <- c(40, 40)       #Mean upper bound for each condition
a_s <- c(0, 0)            #Variability in upper bound for each condition
zp=c(.5, .5)              #Multiplier of a for starting point for condition (Z = a*zp)
zp_s=c(0, 0)              #Variability for starting point multiplier
Nsubs=1                   #Number of subjects
Trials_total=100          #总试次数（交替后每个条件各执行50次）
timeout=500               #Timeout parameter for the random walk

#Create an empty dataframe for storing responses
mydata=data.frame("Sub"=rep(1:Nsubs, each=Trials_total), 
                  "Trial"=rep(1:Trials_total, Nsubs), 
                  "RESPONSE"=NA, 
                  "RT"=NA,
                  "Condition"=NA,
                  "Stimulus"=NA)

for (myperson in 1:Nsubs){
  
  for (i in 1:Trials_total){
    # 根据试次奇偶性交替选择条件：奇数试次用条件1，偶数用条件2
    mycond <- ifelse(i %% 2 == 1, 1, 2)
    
    # 获取当前条件的参数
    condpi=pi[mycond]
    cond_a=mean_a[mycond]
    cond_a_s=a_s[mycond]
    cond_zp=zp[mycond]
    cond_zp_s=zp_s[mycond]
    cond_stim=stim[mycond]
    cond_diff=diff[mycond]
    
    mytrial=i
    
    trial_a=rnorm(1, mean=cond_a, sd=cond_a_s)
    trial_Z=rnorm(1, mean=trial_a*cond_zp, sd=cond_zp_s)
    trial_Pi=rnorm(1, mean=condpi, sd=0)
    
    #Begin setup for random walk
    time=0
    curpointer=trial_Z
    
    #Conduct random walk
    while (time < timeout){
      
      time=time+1
      curpointer=curpointer+sample(c(-1, 1), size=1, prob = c(1-trial_Pi, trial_Pi))
      
      if (curpointer >= trial_a) { 
        myresponse="1"
        break
      } else if (curpointer <= 0){
        myresponse="0"
        break
      }
    }
    
    myRT=abs(time)
    
    #Save the parameters to the respective trial in the dataframe
    row_idx <- which(mydata$Sub==myperson & mydata$Trial==mytrial)
    mydata[row_idx,"RESPONSE"]=myresponse
    mydata[row_idx, "RT"]=myRT
    mydata[row_idx, "Condition"]=mycond
    mydata[row_idx, "Stimulus"]=cond_stim
  }
}

关键修改点 #

• 循环结构调整：移除原有的条件外层循环，改为在试次循环内通过i %% 2 == 1判断奇偶性，动态选择当前条件
• 变量命名优化：将Trials_per_cond改为Trials_total，明确表示总试次数（交替逻辑下每个条件各执行50次）
• 数据框初始化优化：提前声明Condition和Stimulus列，避免后续赋值时自动转换类型
• 索引效率优化：用which()提前定位目标行索引，替代重复的逻辑判断

修复后输出示例 #

|Sub|Trial|RESPONSE|RT  |Condition|Stimulus|
|1  |1    | 1      |102 |    1    |  R     |
|1  |2    | 1      |111 |    2    |  L     |
|1  |3    | 1      |65  |    1    |  R     |
|...|...  | ...    |... |   ...   |  ...   |
|1  |98   | 1      |98  |    2    |  L     |
|1  |99   | 1      |120 |    1    |  R     |
|1  |100  | 1      |100 |    2    |  L     |

内容的提问来源于stack exchange，提问作者Paul