懿说学区（1） | SPSS统计分析（10）多重响应分析

懿说学区（1） | SPSS统计分析（10）多重响应分析

Yishuo school district (1) | SPSS statistical analysis (10) multiple response analysis

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懿说学区（1） | SPSS统计分析（10）多重响应分析

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Yishuo school district (1) | SPSS statistical analysis (10) multiple response analysis

大家好，这里是小编。从今天开始，SPSS系列推文将会放入懿说学区系列进行更新，欢迎大家继续访问学苑内容，我们将竭诚为您带来更多更好的内容分享。

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SPSS统计分析

上一期我们讲述了关于SPSS解决交叉表分析的内容，这一期我们开了新的系列，就来讲一讲SPSS的多重响应分析。

In the last issue, we talked about how SPSS solves the cross table analysis. In this issue, we opened a new series and talked about SPSS multiple response analysis.

首先，我们不妨先来看一看我们日常生活中接触到的一些问卷调查，有些问卷调查的问题是有着多个可选项、允许多选的，多选项问题在问卷调查中其实是普遍存在的，这就带来了一个问题，那就是如何分析这些多个选项的问卷数据。

First of all, we might as well take a look at some of the questionnaire surveys we come across in our daily life. Some questionnaire questions have multiple options and allow multiple choices. In fact, multi-choice questions are common in questionnaire surveys, which brings about a problem, that is, how to analyze the questionnaire data of these multiple options.

多重响应分析就是针对多选项问题的分析方法，又叫做多选项分析。多选项问题一般来说要求答案都是序号变量或者是名义变量，并且允许选择的答案有多个。SPSS中的每一个变量的值我们知道是只能保存一个值，无法处理多选项问题中的多个答案的问题。

Multiple response analysis (MRA) is an analysis method for multi option problems, which is also called multi option analysis. Generally speaking, multi-choice questions require that the answers are sequence number variables or nominal variables, and multiple answers are allowed to be selected. We know that the value of each variable in SPSS can only save one value, and we cannot handle multiple answers in multi-choice questions.

所谓的多重响应分析，就是将一个多选项问题分解成若干个问题，对应设置若干个SPSS可识别的变量，分别存放描述这些问题的几个可能被选择的答案。从而转化为对多个SPSS变量的分析。

The so-called multiple response analysis is to decompose a multi-option problem into several questions, set several SPSS identifiable variables correspondingly, and store several possible answers to these questions. Thus, it can be transformed into the analysis of multiple SPSS variables.

多选项问题的分解通常有两种方法：

1. 多选项二分法

多选项二分法类似于数学上的0-1分布，将多选项问题的每一个答案都视为一个新的变量，每个变量都只取0或1，分别表示选择该答案或者没有选择该答案。

2. 多选项分类法

基本思想是估计多选项问题最多可能出现的答案个数，然后为每个答案定义一个SPSS变量值，变量取值为多选项问题中的可选答案。

There are usually two methods for decomposition of multi option problems:

one Multi option dichotomy

The multi-choice dichotomy is similar to the 0-1 distribution in mathematics. Each answer to the multi-choice question is regarded as a new variable, and each variable only takes 0 or 1, which means that the answer is selected or not selected respectively.

two Multi option taxonomy

The basic idea is to estimate the maximum number of possible answers to the multi-choice question, and then define an SPSS variable value for each answer. The variable value is the optional answer in the multi-choice question.

同样的，我们通过一个案例来具体了解一下如何去做多重响应分析：

Similarly, let's learn how to perform multiple response analysis through a case:

（1） 首先，第一步是要先分解多选项问题，定义多选项的变量集。

这里选择的案例是关于消费者所拥有的数码产品的种类，我们按照二分法去分解这个问题，然后在SPSS里面定义相关的多重响应集。

(1) First, the first step is to decompose the multi option problem and define the variable set of multi options.

The case selected here is about the types of digital products owned by consumers. We decompose this problem according to the dichotomy, and then define the relevant multiple response sets in SPSS.

（2） 第二步，进行多重响应交叉分组下的交叉表分析：

将多选项集添加到交叉表的行、列向量之中。

(2) Step 2: perform cross table analysis under cross grouping of multiple responses:

Add the multi option set to the row and column vectors of the crosstab.

（3） 第三步，输出主要结果并加以分析：

在本案例中，多重响应分析的输出结果是个案摘要和交叉表分析结果表，从结果上看：男性拥有数码产品的数量要高于女性，而在各类数码产品中，拥有MP3的人数是最多的。

(3) Step 3: output and analyze the main results:

In this case, the output of the multiple response analysis is the case summary and the cross table analysis result table. From the results, the number of men owning digital products is higher than that of women, and the number of MP3 players is the largest among all kinds of digital products.

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That's all for today's sharing. If you have unique ideas about today's article, please leave us a message. Let's meet tomorrow. I wish you a happy day today!

That's all for today's sharing. If you have unique ideas about today's article, please leave us a message. Let's meet tomorrow. I wish you a happy day today!

参考资料：百度百科、《SPSS 23统计分析实用教程》

翻译：百度翻译

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