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lianxh
命令发布了:
随时搜索推文、Stata 资源。安装:
. ssc install lianxh
详情参见帮助文件 (有惊喜):
. help lianxh
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⛳ Stata 系列推文:
作者:姜昊 (华东师范大学)
邮箱:HaoJiang0204@outlook.com
目录
table1_mc
是 Phil Clayton 编写的外部命令,用于为论文制定一个特征性事实描述的表格。
* 命令安装
ssc install table1_mc, replace
* 命令语法
table1_mc [if] [in] [weight], vars(var_spec) [options]
var_spec = varname vartype [%fmt1 [%fmt2]] [ \ varname vartype [%fmt1 [%fmt2]] \ ...]
默认情况下,table1_mc
会输出指定变量的基线特征结果。var_spec
用于指定的变量集合,其中:
varname
:指定单个变量,若进行多个变量的分析需要用反斜杠 \
隔开;vartype
:指定描述变量的类型,且不可省略,否则代码报错。具体包括以下 7 种变量类型:
contn
:用于服从正态分布的连续变量,返回均值和标准误;contln
:用于服从对数正态分布的连续变量,返回几何平均值和几何标准误;conts
:用于不服从正态分布与对数正态分布的连续变量,返回中位数与上下四分位数;cat
:类别变量,采用 Pearson 卡方检验组别差异;cate
:类别变量,采用 Fisher 精确检验组别差异;bin
:二分类变量,采用 Pearson 卡方检验组别差异;bine
:二分类变量,采用 Fisher 精确检验组别差异;%fmt1
:变量结果输出格式设定,参考 format
的输出语法;%fmt2
:变量其他结果输出格式设定,参考 format
的输出语法。options
如下:
by(varname)
:分组变量,且 varname
必须是字符串或者数字,并且仅包含非负整数,无论是否增加值标签;missing
:对于 cat
和 cate
的类别变量,将缺失值视为一个新的类别;test
:结果包括描述显著性检验的方法;statistic
:结果包括描述检验统计量值的列;percent
:报告二 (多) 分类变量在所属组别的比重;percent_n
:以 %(n) 格式报告二 (多) 分类变量在所属组别的比重与个数;slashN
:以 n/N 替代 n (%) 的格式报告二 (多) 分类变量在所属组别的统计内容;catrowperc
:报告多分类变量在不同组别的行百分比;pdp(#)
:设定 saving(filename [, export_excel_options])
:设定输出到 Excel 中的文件名与其他选项;clear
: 将 Stata 内存数据集用 table1_mc
结果替换。
为了进一步直观感受各个选项的作用,下文将选取汽车数据 (auto.dta) 进行案例演示。具体地,按照汽车是否属于国产 (用 foreign 变量衡量),分别对服从正态分布的 weight、服从对数正态分布的 price、不服从正态分布与对数正态分布的 mpg、多分类变量 rep78 和二分类变量 much_headroom 进行分析。
. sysuse auto, clear
. generate much_headroom = (headroom>=3)
. table1_mc, by(foreign) vars(weight contn %5.0f \ price contln %5.0f %4.2f ///
> \ mpg conts %5.0f \ rep78 cate \ much_headroom bin) onecol nospace
+--------------------------------------------+
| factor N_0 N_1 m_0 m_1 |
|--------------------------------------------|
| Weight (lbs.) 52 22 0 0 |
|--------------------------------------------|
| Price 52 22 0 0 |
|--------------------------------------------|
| Mileage (mpg) 52 22 0 0 |
|--------------------------------------------|
| Repair record 1978 48 21 4 1 |
|--------------------------------------------|
| much_headroom 52 22 0 0 |
+--------------------------------------------+
N_ ... #records used below, m_ ... #records not used
+--------------------------------------------------------------+
| Domestic Foreign p-value |
|--------------------------------------------------------------|
| N=52 N=22 |
|--------------------------------------------------------------|
| Weight (lbs.) 3317 (695) 2316 (433) <0.001 |
|--------------------------------------------------------------|
| Price 5534 (×/1.50) 5959 (×/1.44) 0.46 |
|--------------------------------------------------------------|
| Mileage (mpg) 19 (17-22) 25 (21-28) 0.002 |
|--------------------------------------------------------------|
| Repair record 1978 <0.001 |
| 1 2 (4%) 0 (0%) |
| 2 8 (17%) 0 (0%) |
| 3 27 (56%) 3 (14%) |
| 4 9 (19%) 9 (43%) |
| 5 2 (4%) 9 (43%) |
|--------------------------------------------------------------|
| much_headroom 35 (67%) 8 (36%) 0.014 |
+--------------------------------------------------------------+
Data are presented as mean (SD) or geometric mean (×/geometric SD) or
median (IQR) for continuous measures, and n (%) for categorical measures.
增加 missing
选项,则变量 rep78 的缺失值被识别为新的类别。
. table1_mc, by(foreign) vars(weight contn %5.0f \ price contln %5.0f %4.2f ///
> \ mpg conts %5.0f \ rep78 cate \ much_headroom bin) onecol nospace missing
+--------------------------------------------+
| factor N_0 N_1 m_0 m_1 |
|--------------------------------------------|
| Weight (lbs.) 52 22 0 0 |
|--------------------------------------------|
| Price 52 22 0 0 |
|--------------------------------------------|
| Mileage (mpg) 52 22 0 0 |
|--------------------------------------------|
| Repair record 1978 52 22 0 0 |
|--------------------------------------------|
| much_headroom 52 22 0 0 |
+--------------------------------------------+
N_ ... #records used below, m_ ... #records not used
+--------------------------------------------------------------+
| Domestic Foreign p-value |
|--------------------------------------------------------------|
| N=52 N=22 |
|--------------------------------------------------------------|
| Weight (lbs.) 3317 (695) 2316 (433) <0.001 |
|--------------------------------------------------------------|
| Price 5534 (×/1.50) 5959 (×/1.44) 0.46 |
|--------------------------------------------------------------|
| Mileage (mpg) 19 (17-22) 25 (21-28) 0.002 |
|--------------------------------------------------------------|
| Repair record 1978 <0.001 |
| 1 2 (4%) 0 (0%) |
| 2 8 (15%) 0 (0%) |
| 3 27 (52%) 3 (14%) |
| 4 9 (17%) 9 (41%) |
| 5 2 (4%) 9 (41%) |
| Missing 4 (8%) 1 (5%) |
|--------------------------------------------------------------|
| much_headroom 35 (67%) 8 (36%) 0.014 |
+--------------------------------------------------------------+
Data are presented as mean (SD) or geometric mean (×/geometric SD)
or median (IQR) for continuous measures, and n (%) for categorical measures.
增加 test
选项,每行结果后增加了显著性检验的方法。
. table1_mc, by(foreign) vars(weight contn %5.0f \ price contln %5.0f %4.2f ///
> \ mpg conts %5.0f \ rep78 cate \ much_headroom bin) onecol nospace missing test
+--------------------------------------------+
| factor N_0 N_1 m_0 m_1 |
|--------------------------------------------|
| Weight (lbs.) 52 22 0 0 |
|--------------------------------------------|
| Price 52 22 0 0 |
|--------------------------------------------|
| Mileage (mpg) 52 22 0 0 |
|--------------------------------------------|
| Repair record 1978 52 22 0 0 |
|--------------------------------------------|
| much_headroom 52 22 0 0 |
+--------------------------------------------+
N_ ... #records used below, m_ ... #records not used
+-----------------------------------------------------------------------------------+
| Domestic Foreign Test p-value |
|-----------------------------------------------------------------------------------|
| N=52 N=22 |
|-----------------------------------------------------------------------------------|
| Weight (lbs.) 3317 (695) 2316 (433) Ind. t test <0.001 |
|-----------------------------------------------------------------------------------|
| Price 5534 (×/1.50) 5959 (×/1.44) Ind. t test, logged data 0.46 |
|-----------------------------------------------------------------------------------|
| Mileage (mpg) 19 (17-22) 25 (21-28) Wilcoxon rank-sum 0.002 |
|-----------------------------------------------------------------------------------|
| Repair record 1978 Fisher's exact <0.001 |
| 1 2 (4%) 0 (0%) |
| 2 8 (15%) 0 (0%) |
| 3 27 (52%) 3 (14%) |
| 4 9 (17%) 9 (41%) |
| 5 2 (4%) 9 (41%) |
| Missing 4 (8%) 1 (5%) |
|-----------------------------------------------------------------------------------|
| much_headroom 35 (67%) 8 (36%) Chi-square 0.014 |
+-----------------------------------------------------------------------------------+
Data are presented as mean (SD) or geometric mean (×/geometric SD) or median (IQR) for
continuous measures, and n (%) for categorical measures.
增加 statistic
选项,每行结果后增加了检验统计量值。
. table1_mc, by(foreign) vars(weight contn %5.0f \ price contln %5.0f %4.2f ///
> \ mpg conts %5.0f \ rep78 cate \ much_headroom bin) onecol nospace missing test statistic
+--------------------------------------------+
| factor N_0 N_1 m_0 m_1 |
|--------------------------------------------|
| Weight (lbs.) 52 22 0 0 |
|--------------------------------------------|
| Price 52 22 0 0 |
|--------------------------------------------|
| Mileage (mpg) 52 22 0 0 |
|--------------------------------------------|
| Repair record 1978 52 22 0 0 |
|--------------------------------------------|
| much_headroom 52 22 0 0 |
+--------------------------------------------+
N_ ... #records used below, m_ ... #records not used
+-----------------------------------------------------------------------------------------------+
| Domestic Foreign Test Statistic p-value |
|-----------------------------------------------------------------------------------------------|
| N=52 N=22 |
|-----------------------------------------------------------------------------------------------|
| Weight (lbs.) 3317 (695) 2316 (433) Ind. t test t(72)= 6.25 <0.001 |
|-----------------------------------------------------------------------------------------------|
| Price 5534 (×/1.50) 5959 (×/1.44) Ind. t test, logged data t(72)= -0.74 0.46 |
|-----------------------------------------------------------------------------------------------|
| Mileage (mpg) 19 (17-22) 25 (21-28) Wilcoxon rank-sum Z= -3.10 0.002 |
|-----------------------------------------------------------------------------------------------|
| Repair record 1978 Fisher's exact N/A <0.001 |
| 1 2 (4%) 0 (0%) |
| 2 8 (15%) 0 (0%) |
| 3 27 (52%) 3 (14%) |
| 4 9 (17%) 9 (41%) |
| 5 2 (4%) 9 (41%) |
| Missing 4 (8%) 1 (5%) |
|-----------------------------------------------------------------------------------------------|
| much_headroom 35 (67%) 8 (36%) Chi-square Chi2(1)= 6.08 0.014 |
+-----------------------------------------------------------------------------------------------+
Data are presented as mean (SD) or geometric mean (×/geometric SD) or median (IQR) for continuous
measures, and n (%) for categorical measures.
增加 saving
选项将结果保存至指定位置,并利用 clear
选项将 Stata 内存中数据用输出结果替换。
. table1_mc, by(foreign) vars(weight contn %5.0f \ price contln %5.0f %4.2f ///
> \ mpg conts %5.0f \ rep78 cate \ much_headroom bin) onecol nospace ///
> missing test statistic saving("Table 1.xlsx", replace) clear
file Table 1.xlsx saved
Note:产生如下推文列表的 Stata 命令为:
lianxh 统计, m
安装最新版lianxh
命令:
ssc install lianxh, replace
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New!
lianxh
和songbl
命令发布了:
随时搜索连享会推文、Stata 资源,安装命令如下:
. ssc install lianxh
使用详情参见帮助文件 (有惊喜):
. help lianxh