blocks|key|5335139|text|这样如何：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|5335140|reg<-lm(formula(paste(depvar+,'~++var1+%2B+var2')),+data=mydata)|code-block|syntax|javascript|5335141|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|I|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|J|8|@]|9|@]|A|$E|F]]|$1|G|3|-4|5|6|7|K|8|@]|9|@]|A|$]]]|H|$]]

how about this:

<pre><code>reg&lt;-lm(formula(paste(depvar ,'~ var1 + var2')), data=mydata)
</code></pre>

blocks|key|3018468|text|让我提供另一种解决方案，因为不需要通过必须解析的字符串来绕过概念：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|3018469|R允许您通过一组函数(如substitute或bquote+)在运行时操作表达式(也就是说，无需将其编码为字符串)。bquote可能是最接近SAS的方法：|offset|length|style|CODE|3018470|depvar+=+quote(sales.int)
reg+=+lm(bquote(.(depvar)+~+var1+%2B+var2),+mydata)|code-block|syntax|javascript|3018471|bquote本质上接受一个R表达式，并将.(…)周围的每个变量替换为它的值。第一行指定一个变量的名称-这非常类似于SAS中的实际宏。这需要用quote包围，否则R会尝试将sales.int的内容赋值给depvar，而不是它的名称。除了不能在其中使用.(…)语法替换现有变量之外，quote的工作方式与bquote相同。|3018472|您还可以根据用户输入确定此名称(即，通过使用as.name从字符串确定|3018473|depvar+=+as.name('sales.int')|3018474|as.name将字符串转换为R对象名称。|3018475|3018476|只是对语言设计的评论，因为这是一个常见的误解:在这方面，R可能不像SAS那么直观，但它在概念上更一致，而且普遍适用。非R统计包本质上提供了围绕语言工作的技巧，而R则将公式完美地集成到语言本身中。|3018477|entityMap|0|LINK|mutability|MUTABLE|url|https://stat.ethz.ch/R-manual/R-devel/library/base/html/substitute.html|1|https://stat.ethz.ch/R-manual/R-devel/library/base/html/bquote.html|2|3|https://stat.ethz.ch/R-manual/R-devel/library/base/html/name.html^0|0|C|A|N|6|1M|6|C|A|0|N|6|1|0|0|0|6|K|4|1Y|5|2D|9|2S|6|3G|4|3V|5|46|6|3V|5|2|0|M|7|0|0|0|7|0|7|3|0|0|0^^$0|@$1|2|3|4|5|6|7|1A|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|1B|8|@$D|1C|E|1D|F|G]|$D|1E|E|1F|F|G]|$D|1G|E|1H|F|G]]|9|@$D|1I|E|1J|1|1K]|$D|1L|E|1M|1|1N]]|A|$]]|$1|H|3|I|5|J|7|1O|8|@]|9|@]|A|$K|L]]|$1|M|3|N|5|6|7|1P|8|@$D|1Q|E|1R|F|G]|$D|1S|E|1T|F|G]|$D|1U|E|1V|F|G]|$D|1W|E|1X|F|G]|$D|1Y|E|1Z|F|G]|$D|20|E|21|F|G]|$D|22|E|23|F|G]|$D|24|E|25|F|G]]|9|@$D|26|E|27|1|28]]|A|$]]|$1|O|3|P|5|6|7|29|8|@$D|2A|E|2B|F|G]]|9|@]|A|$]]|$1|Q|3|R|5|J|7|2C|8|@]|9|@]|A|$K|L]]|$1|S|3|T|5|6|7|2D|8|@$D|2E|E|2F|F|G]]|9|@$D|2G|E|2H|1|2I]]|A|$]]|$1|U|3|-4|5|6|7|2J|8|@]|9|@]|A|$]]|$1|V|3|W|5|6|7|2K|8|@]|9|@]|A|$]]|$1|X|3|-4|5|6|7|2L|8|@]|9|@]|A|$]]]|Y|$Z|$5|10|11|12|A|$13|14]]|15|$5|10|11|12|A|$13|16]]|17|$5|10|11|12|A|$13|14]]|18|$5|10|11|12|A|$13|19]]]]

Let me provide an alternative solution, because there’s no need to go the conceptual detour via character strings which have to be parsed:

R allows you to manipulate expressions at runtime (without encoding them as strings, that is), via a set of functions such as <a href="https://stat.ethz.ch/R-manual/R-devel/library/base/html/substitute.html" rel="noreferrer"><code>substitute</code></a> or <a href="https://stat.ethz.ch/R-manual/R-devel/library/base/html/bquote.html" rel="noreferrer"><code>bquote</code></a>. <code>bquote</code> probably comes closest to the SAS approach:

<pre><code>depvar = quote(sales.int)
reg = lm(bquote(.(depvar) ~ var1 + var2), mydata)
</code></pre>

<code>bquote</code> essentially takes an R expression, and replaces every variable which is surrounded by <code>.(…)</code> by its value. The first line assigns a name to a variable – this is very similar to the actual macro in SAS. This needs to be surrounded by <code>quote</code>, because otherwise R would try to assign the contents of <code>sales.int</code> to <code>depvar</code>, rather than its name. <a href="https://stat.ethz.ch/R-manual/R-devel/library/base/html/substitute.html" rel="noreferrer"><code>quote</code></a> works identical to <code>bquote</code>, except that you cannot use the <code>.(…)</code> syntax in it to replace existing variables.

You can also determine this name from a user input (i.e. from a character string, by using <code>as.name</code>:

<pre><code>depvar = as.name('sales.int')
</code></pre>

<a href="https://stat.ethz.ch/R-manual/R-devel/library/base/html/name.html" rel="noreferrer"><code>as.name</code></a> converts a character string to an R object name.

<hr>

Just a comment on the language design, since this a common misunderstanding: R may be less intuitive than SAS in this regard, but it‘s conceptually much more consistent and generally applicable. Non-R statistics packages essentially provide hacks to work around the language while R integrates formulae beautifully into the language itself.

blocks|key|757945|text|它们都不起作用。虽然可以使用new=as.name("+f3+")或new=quote(f3)来引用f3，但在SAS中使用&可以调用宏变量，但在R中没有使用类似的&。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|757946|>+test<-data.frame(f1=c(1,2),+f2=c("a","b"));+test
#+++f1+f2
#1++1++a
#2++2++b

>+new=as.name("f3");+new;+
#f3
>+new=quote(f3);+new;+
#f3

>+#+you+still+get+new+rather+than+f3+as+expected
>+new<-test$f1;+
>+new
#[1]+1+2|code-block|syntax|javascript|757947|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|I|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|J|8|@]|9|@]|A|$E|F]]|$1|G|3|-4|5|6|7|K|8|@]|9|@]|A|$]]]|H|$]]

None of them works. The macro variable is invoked with &amp; in SAS but no similar &amp; being used in R although you can use new=as.name("f3") or new=quote(f3) to refer to f3 as shown below.

<pre><code>&gt; test&lt;-data.frame(f1=c(1,2), f2=c("a","b")); test
# f1 f2
#1 1 a
#2 2 b

&gt; new=as.name("f3"); new; 
#f3
&gt; new=quote(f3); new; 
#f3

&gt; # you still get new rather than f3 as expected
&gt; new&lt;-test$f1; 
&gt; new
#[1] 1 2
</code></pre>

How do I assign a macro variable in R?

In SAS, I would use the following code

<pre><code>%LET DEPVAR = sales_ind

PROC REG DATA=mydata;
MODEL &amp;DEPVAR = VAR1 + VAR2;
RUN;
</code></pre>

However, in R, I am struggling to do something similar (this doesn't work)

<pre><code>depvar &lt;&lt;- sales_ind

reg&lt;-lm(depvar ~ var1 + var2, data=mydata)
</code></pre>

Any ideas?

Thank you!

How do I use a macro variable in R? (Similar to %LET in SAS)

翻译质量差，导致语言生硬或混乱。

没有提供实际的解决方法或示例。

解答不清晰，无法理解或解决问题。

页面排版不美观，阅读体验差。

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如何在R中赋值宏变量？在SAS中，我将使用以下代码%LET DEPVAR = sales_indPROC REG DATA=mydata;MODEL &DEPVAR = VAR1 + VAR2;RUN;然而，在R中，我正在努力做一些类似的事情(这不起作用)depvar <<- sales_indreg<-lm(depv...

问如何在R中使用宏变量？(类似于SAS中的%LET )
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问如何在R中使用宏变量？(类似于SAS中的%LET )EN