我正在尝试计算某些时间范围内的KPI值 - 响应率，转换率和收益率。我需要使用SAS来做到这一点。这是我正在寻找的理想输出：
MTD/YTD Dates Tactic Response Rate Conversion Rate Yield Rate
Last 3 Month Performance 11/1/13-1/31/14 ProspectDM 0.303% 27.2% 0.082%
Last 3 Month Performance 11/1/13-1/31/14 AcquisitionDM 0.486% 30.1% 0.146%
Last 3 Month Performance 11/1/13-1/31/14 ProspectBAU 0.248% 25.2% 0.063%
2014 YTD Performance 1/1/14-1/31/14 ProspectDM 0.173% 25.1% 0.043%
2014 YTD Performance 1/1/14-1/31/14 AcquisitionDM 0.464% 28.9% 0.134%
2014 YTD Performance 1/1/14-1/31/14 ProspectBAU 0.123% 21.4% 0.026%
2013 Performance 1/1/13-12/31/13 ProspectDM 0.412% 25.7% 0.106%
2013 Performance 1/1/13-12/31/13 AcquisitionDM 0.648% 28.4% 0.184%
2013 Performance 1/1/13-12/31/13 ProspectBAU 0.324% 23.6% 0.076%
我有这个计算KPI的程序：
data have;
set want;
Response_Rate=round((Calls/Mailed),0.00001) ;
Conversion_Rate=round((Sales / Calls),0.00001);
Yield=round((Sales /Mailed),0.00001);
Label
Response_Rate='Response Rate'
Conversion_Rate='Conversion Rate'
Yield='Yield Rate';
format Response_Rate Conversion_Rate Yield Percent10.2;
run;
我遇到的问题是如何计算它们的时间范围1.最近3个月的表现，2。年初表现，以及3.前一年的战术表现。我还需要一个日期范围变量来连接日期范围。我熟悉intnx函数：
drop_date between &start and intnx('month',&start,-3,"Sameday")
drop_date between &start and intnx('year',&start,-1,"Sameday");
以下是一些示例数据。任何帮助将不胜感激。谢谢！
data have;
length Insertion 8 tactic $13;
INPUT Insertion :anydtdte9. tactic $ Mailed Calls Sales ;
format Insertion date9.;
datalines;
3/2/2013 ProspectDM 167 53 19
4/6/2013 ProspectDM 216 65 12
2/23/2013 ProspectDM 153 73 26
5/11/2013 ProspectDM 207 64 4
5/4/2013 ProspectDM 209 69 15
6/22/2013 ProspectDM 123 69 8
1/26/2013 ProspectDM 109 59 22
2/9/2013 ProspectDM 121 56 1
2/2/2013 ProspectDM 182 63 21
1/19/2013 ProspectDM 151 57 11
6/8/2013 ProspectDM 171 57 27
6/15/2013 ProspectDM 170 68 14
4/20/2013 ProspectDM 167 50 17
3/9/2013 ProspectDM 168 66 17
5/18/2013 ProspectDM 141 50 28
8/17/2013 ProspectDM 217 67 13
9/21/2013 ProspectDM 193 63 3
5/25/2013 ProspectDM 161 57 22
1/4/2014 ProspectDM 182 51 18
9/14/2013 ProspectDM 124 72 16
6/1/2013 ProspectDM 118 52 20
6/29/2013 ProspectDM 115 69 22
8/31/2013 ProspectDM 146 67 16
8/3/2013 ProspectDM 157 67 3
1/11/2014 ProspectDM 183 62 3
1/18/2014 ProspectDM 206 74 8
9/7/2013 ProspectDM 168 74 28
12/28/2013 ProspectDM 201 71 16
10/12/2013 ProspectDM 133 59 24
2/1/2014 AcquisitionDM 176 50 23
1/25/2014 AcquisitionDM 136 68 20
2/16/2013 AcquisitionDM 122 66 10
8/24/2013 AcquisitionDM 190 50 22
9/28/2013 AcquisitionDM 210 63 8
12/21/2013 AcquisitionDM 111 58 8
3/30/2013 AcquisitionDM 156 70 19
4/13/2013 AcquisitionDM 149 66 28
5/11/2013 AcquisitionDM 149 60 20
5/18/2013 AcquisitionDM 164 63 7
6/22/2013 AcquisitionDM 151 60 20
3/16/2013 AcquisitionDM 182 66 22
3/9/2013 AcquisitionDM 106 61 19
4/27/2013 AcquisitionDM 140 72 29
6/1/2013 AcquisitionDM 122 55 11
5/25/2013 AcquisitionDM 109 54 19
1/4/2014 AcquisitionDM 113 65 11
11/16/2013 AcquisitionDM 160 57 30
12/7/2013 AcquisitionDM 114 64 17
12/14/2013 AcquisitionDM 98 61 26
1/18/2014 AcquisitionDM 147 71 9
4/6/2013 AcquisitionDM 152 52 29
12/1/2013 AcquisitionDM 215 72 14
12/15/2013 AcquisitionDM 209 61 25
1/12/2013 AcquisitionDM 175 75 21
2/23/2013 AcquisitionDM 101 66 8
3/30/2013 AcquisitionDM 153 57 4
1/5/2013 AcquisitionDM 180 74 29
11/24/2013 AcquisitionDM 156 50 20
5/11/2013 AcquisitionDM 122 68 17
12/29/2013 AcquisitionDM 198 70 20
4/13/2013 AcquisitionDM 111 55 21
5/4/2013 AcquisitionDM 97 56 6
4/27/2013 AcquisitionDM 124 66 19
6/15/2013 AcquisitionDM 174 67 27
12/22/2013 AcquisitionDM 142 58 22
6/1/2013 AcquisitionDM 183 65 4
7/20/2013 AcquisitionDM 181 66 4
3/9/2013 AcquisitionDM 144 68 15
5/4/2013 AcquisitionDM 97 59 18
7/27/2013 AcquisitionDM 199 54 5
4/13/2013 AcquisitionDM 118 56 1
8/24/2013 AcquisitionDM 153 51 2
3/16/2013 AcquisitionDM 136 67 13
8/31/2013 AcquisitionDM 96 57 19
4/27/2013 AcquisitionDM 184 66 15
6/29/2013 AcquisitionDM 119 55 3
5/18/2013 AcquisitionDM 111 74 5
4/20/2013 AcquisitionDM 192 72 15
4/20/2013 AcquisitionDM 153 69 30
9/28/2013 AcquisitionDM 164 50 26
9/28/2013 AcquisitionDM 192 55 21
8/3/2013 AcquisitionDM 163 51 11
12/7/2013 AcquisitionDM 209 58 15
6/22/2013 AcquisitionDM 101 55 3
10/26/2013 AcquisitionDM 171 74 11
7/6/2013 AcquisitionDM 172 61 3
11/2/2013 AcquisitionDM 153 68 6
5/25/2013 AcquisitionDM 124 55 2
9/7/2013 AcquisitionDM 144 66 20
8/10/2013 AcquisitionDM 135 69 9
11/30/2013 AcquisitionDM 181 57 18
10/5/2013 AcquisitionDM 104 60 13
10/19/2013 AcquisitionDM 115 50 16
11/23/2013 AcquisitionDM 209 53 30
1/25/2014 AcquisitionDM 137 63 22
8/24/2013 AcquisitionDM 141 50 23
8/17/2013 AcquisitionDM 152 64 8
9/14/2013 AcquisitionDM 106 61 7
11/16/2013 AcquisitionDM 169 60 11
10/12/2013 AcquisitionDM 112 65 15
9/21/2013 AcquisitionDM 173 73 26
10/5/2013 AcquisitionDM 175 53 1
12/21/2013 AcquisitionDM 104 68 28
2/1/2014 AcquisitionDM 113 62 30
7/14/2013 AcquisitionDM 114 73 28
7/28/2013 AcquisitionDM 193 59 26
9/22/2013 AcquisitionDM 187 55 15
7/14/2013 AcquisitionDM 214 58 13
8/11/2013 AcquisitionDM 151 52 12
12/1/2013 AcquisitionDM 106 60 21
12/15/2014 AcquisitionDM 105 55 27
8/18/2013 AcquisitionDM 101 67 24
1/19/2013 AcquisitionDM 185 55 1
1/26/2013 AcquisitionDM 208 60 24
3/9/2013 AcquisitionDM 129 65 14
9/29/2013 AcquisitionDM 185 66 2
12/8/2013 AcquisitionDM 149 68 10
3/2/2013 AcquisitionDM 192 58 3
2/23/2013 AcquisitionDM 146 72 21
12/29/2013 AcquisitionDM 209 53 28
4/13/2013 AcquisitionDM 213 56 20
12/1/2013 AcquisitionDM 140 64 15
2/2/2013 AcquisitionDM 128 75 3
3/30/2013 AcquisitionDM 135 68 12
5/18/2013 AcquisitionDM 140 52 20
12/22/2013 AcquisitionDM 206 66 15
1/5/2013 AcquisitionDM 119 63 20
6/1/2013 AcquisitionDM 126 73 2
2/9/2013 ProspectBAU 175 59 12
6/8/2013 ProspectBAU 190 51 12
4/27/2013 ProspectBAU 107 54 19
7/13/2013 ProspectBAU 137 54 27
2/16/2013 ProspectBAU 192 68 8
3/16/2013 ProspectBAU 101 63 3
5/18/2013 ProspectBAU 156 60 23
6/1/2013 ProspectBAU 142 50 20
9/28/2013 ProspectBAU 168 75 21
4/20/2013 ProspectBAU 187 66 30
5/4/2013 ProspectBAU 126 74 4
3/23/2013 ProspectBAU 152 57 23
8/31/2013 ProspectBAU 108 53 14
11/2/2013 ProspectBAU 154 67 26
5/25/2013 ProspectBAU 201 64 22
10/5/2013 ProspectBAU 107 54 8
6/22/2013 ProspectBAU 204 70 22
8/10/2013 ProspectBAU 128 55 19
9/14/2013 ProspectBAU 130 64 24
6/29/2013 ProspectBAU 147 61 29
12/14/2013 ProspectBAU 97 54 5
1/18/2014 ProspectBAU 97 75 4
12/7/2013 ProspectBAU 158 65 8
8/3/2013 ProspectBAU 178 67 16
1/11/2014 ProspectBAU 97 65 27
9/21/2013 ProspectBAU 147 55 28
10/12/2013 ProspectBAU 126 62 1
2/1/2014 ProspectBAU 158 63 2
7/21/2012 ProspectBAU 95 61 1
11/17/2013 ProspectBAU 157 64 11
12/8/2013 ProspectBAU 133 63 23
1/12/2013 ProspectBAU 167 54 6
4/6/2013 ProspectBAU 172 56 6
7/20/2013 ProspectBAU 110 57 30
8/24/2013 ProspectBAU 174 73 11
9/7/2013 ProspectBAU 157 70 14
1/25/2014 ProspectBAU 178 63 29
1/25/2014 ProspectBAU 178 63 29
;
答案 0 :(得分：0)
我建议您创建一个定义时间段的格式。然后可以与proc means一起使用来生成输出。
为此，您需要了解multilabel formats。也就是说，为一个输入值存储多个值（标签）的格式。基本概念是您为每个报告期限的每个日期值存储标签，然后按此汇总。
例如：
proc format;
value reppd (multilabel notsorted)
'01NOV13'd - '31JAN14'd = "Last 3 Month Performance"
'01JAN14'd - '31DEC14'd = "2014 YTD Performance"
'01JAN13'd - '31DEC13'd = "2013 YTD Performance"
;
quit;
proc means data=have;
class insertion/mlf;
class tactic;
types insertion*tactic;
var response_rate conversion_rate yield;
format insertion reppd.;
run;