Question

我正在使用心理包，我试过以下代码：

library(psych)
str(price_per_d)
Least_appealing <-subset(zdf_base, select=c("price_per_h", 
"price_per_d", "mileage", "one_way_option", "difficulties", 
"vehicle_types", "parking_spot","picking_up","availability", "dirty", 
"returning","refilling", "loalty_programs"))
# code from stackoverflow which I use, to get a numeric x
Least_appealing <- gsub(",", "", Least_appealing)  
Least_appealing <- as.numeric(Least_appealing)

fa.parallel(Least_appealing)

我收到此错误消息：

 > library(psych)
 > str(price_per_d)
 Factor w/ 1 level "Price (daily rate too high)": 1 NA 1 1 1 NA NA 1 1 
 NA ...
 > Least_appealing <-subset(zdf_base, select=c("price_per_h", 
 +                                             "price_per_d", 
 "mileage", "one_way_option", "difficulties", 
 +                                             "vehicle_types", 
 "parking_spot","picking_up","availability", "dirty", 
 +                                             "returning","refilling", 
 "loalty_programs"))
 > 
 > Least_appealing <- gsub(",", "", Least_appealing)  
 > Least_appealing <- as.numeric(Least_appealing)
 **Warnmeldung:
 NAs durch Umwandlung erzeugt** 
> 
> fa.parallel(Least_appealing)
**Fehler in cor(x, use = use) : supply both 'x' and 'y' or a matrix-like 
'x'**
>

如何成功进行因子分析？首先我收到了错误消息，我的＆＃39; x＆＃39;必须是数字，这就是我使用上述代码的原因。当我使用这段代码时，R告诉我，我通过转换得到了NA。我仍然坚持并尝试fa.parallel，这给了我另一个错误信息。有人可以帮忙吗？

Answer 1

我不知道您是否已经解决了这个问题，但是如果您将字符数据与数字数据混合在一起（例如，您的编码是分类的，并且需要将其转换为数字，则可以尝试使用char2numeric函数，然后再使用做fa。

例如包含分类和数值混合数据；

describe(data)  #this will flag those variables that are categorical with an asterix
new.data <- char2numeric(data)  #this makes all numeric
fa(new.data, nfactors=3) #to get three factors

似乎“最小吸引”对象中只有一个变量。

cor中的错误（x，use = use）：同时提供＆＃39; x＆＃39;并且＆＃39; y＆＃39;或类似矩阵＆＃39; x＆＃39;

1 个答案: