topic multiple linear regression in SAS Procedures https://communities.sas.com/t5/SAS-Procedures/multiple-linear-regression/m-p/345520#M63518 <P>I have this program:</P> <P>&nbsp;</P> <P>&nbsp;</P> <PRE><CODE class=" language-sas">proc reg data=TRNSTRANSPOSEDQUERY_FOR_TRNSTRAN; model LOG_ALLWD = ABDOM_HERNIA ADV_DIABETES CHF_CARDIOMYO_VALVDIS CHRON_RENAL_FAIL DEP_BIPOLAR_PARA DIAG_W_ADD DVT_PE GASTRDUO_ULCER GAST_DUODENITIS GI_BLEED HEP_CIRR_OTR_LIVER IBS INTEST_OBSTR MILD_SLEEP_APNEA NUTR_OTR_ANEMIA RESP_FAILURE RHEU_ARTH SCREEN_W_ADD SHOCK_SYNC STROKE_PARAL TOBACCO / SELECTION=BACKWARD SLS=0.15 ALPHA=0.1 ; title "Backward Selection Model"; run; quit;</CODE></PRE> <P>&nbsp;</P> <P>and got this report: I want to save this report to a sas data set in the same format. I used the option outset=estimate and did not get what I want. Do you have a way to do this? Thanks!</P> <DIV>Variable Parameter<BR />Estimate Standard<BR />Error Type&nbsp;II&nbsp;SS F Value Pr&nbsp;&gt;&nbsp;F <TABLE cellspacing="0" cellpadding="0"> <TBODY> <TR> <TD>Intercept</TD> <TD>7.05997</TD> <TD>0.00517</TD> <TD>151738</TD> <TD>1863176</TD> <TD>&lt;.0001</TD> </TR> <TR> <TD>ABDOM_HERNIA</TD> <TD>0.11768</TD> <TD>0.04140</TD> <TD>0.65785</TD> <TD>8.08</TD> <TD>0.0045</TD> </TR> <TR> <TD>ADV_DIABETES</TD> <TD>0.03687</TD> <TD>0.01479</TD> <TD>0.50618</TD> <TD>6.22</TD> <TD>0.0127</TD> </TR> <TR> <TD>CHF_CARDIOMYO_VALVDIS</TD> <TD>0.09931</TD> <TD>0.02582</TD> <TD>1.20509</TD> <TD>14.80</TD> <TD>0.0001</TD> </TR> <TR> <TD>CHRON_RENAL_FAIL</TD> <TD>0.11154</TD> <TD>0.04609</TD> <TD>0.47694</TD> <TD>5.86</TD> <TD>0.0155</TD> </TR> <TR> <TD>DEP_BIPOLAR_PARA</TD> <TD>0.09403</TD> <TD>0.02506</TD> <TD>1.14656</TD> <TD>14.08</TD> <TD>0.0002</TD> </TR> <TR> <TD>DIAG_W_ADD</TD> <TD>0.30107</TD> <TD>0.00906</TD> <TD>89.88892</TD> <TD>1103.74</TD> <TD>&lt;.0001</TD> </TR> <TR> <TD>DVT_PE</TD> <TD>0.05880</TD> <TD>0.03807</TD> <TD>0.19423</TD> <TD>2.38</TD> <TD>0.1225</TD> </TR> <TR> <TD>GASTRDUO_ULCER</TD> <TD>0.04103</TD> <TD>0.03024</TD> <TD>0.14988</TD> <TD>1.84</TD> <TD>0.1750</TD> </TR> <TR> <TD>GAST_DUODENITIS</TD> <TD>0.26914</TD> <TD>0.01104</TD> <TD>48.38799</TD> <TD>594.15</TD> <TD>&lt;.0001</TD> </TR> <TR> <TD>GI_BLEED</TD> <TD>0.08496</TD> <TD>0.01131</TD> <TD>4.59823</TD> <TD>56.46</TD> <TD>&lt;.0001</TD> </TR> <TR> <TD>HEP_CIRR_OTR_LIVER</TD> <TD>0.14005</TD> <TD>0.02110</TD> <TD>3.58960</TD> <TD>44.08</TD> <TD>&lt;.0001</TD> </TR> <TR> <TD>IBS</TD> <TD>0.11712</TD> <TD>0.01032</TD> <TD>10.49936</TD> <TD>128.92</TD> <TD>&lt;.0001</TD> </TR> <TR> <TD>INTEST_OBSTR</TD> <TD>0.08401</TD> <TD>0.01877</TD> <TD>1.63125</TD> <TD>20.03</TD> <TD>&lt;.0001</TD> </TR> <TR> <TD>MILD_SLEEP_APNEA</TD> <TD>0.04275</TD> <TD>0.01265</TD> <TD>0.92967</TD> <TD>11.42</TD> <TD>0.0007</TD> </TR> <TR> <TD>NUTR_OTR_ANEMIA</TD> <TD>0.14219</TD> <TD>0.01517</TD> <TD>7.15148</TD> <TD>87.81</TD> <TD>&lt;.0001</TD> </TR> <TR> <TD>RESP_FAILURE</TD> <TD>0.14960</TD> <TD>0.02995</TD> <TD>2.03182</TD> <TD>24.95</TD> <TD>&lt;.0001</TD> </TR> <TR> <TD>RHEU_ARTH</TD> <TD>0.02965</TD> <TD>0.01502</TD> <TD>0.31725</TD> <TD>3.90</TD> <TD>0.0485</TD> </TR> <TR> <TD>SCREEN_W_ADD</TD> <TD>0.24392</TD> <TD>0.00721</TD> <TD>93.13549</TD> <TD>1143.60</TD> <TD>&lt;.0001</TD> </TR> <TR> <TD>SHOCK_SYNC</TD> <TD>0.20405</TD> <TD>0.04136</TD> <TD>1.98179</TD> <TD>24.33</TD> <TD>&lt;.0001</TD> </TR> <TR> <TD>STROKE_PARAL</TD> <TD>0.07213</TD> <TD>0.04339</TD> <TD>0.22507</TD> <TD>2.76</TD> <TD>0.0965</TD> </TR> <TR> <TD>TOBACCO</TD> <TD>0.10960</TD> <TD>0.01568</TD> <TD>3.97830</TD> <TD>48.85</TD> <TD>&lt;.0001</TD> </TR> </TBODY> </TABLE> </DIV> Wed, 29 Mar 2017 19:55:10 GMT zhuxiaoyan1 2017-03-29T19:55:10Z multiple linear regression https://communities.sas.com/t5/SAS-Procedures/multiple-linear-regression/m-p/345520#M63518 <P>I have this program:</P> <P>&nbsp;</P> <P>&nbsp;</P> <PRE><CODE class=" language-sas">proc reg data=TRNSTRANSPOSEDQUERY_FOR_TRNSTRAN; model LOG_ALLWD = ABDOM_HERNIA ADV_DIABETES CHF_CARDIOMYO_VALVDIS CHRON_RENAL_FAIL DEP_BIPOLAR_PARA DIAG_W_ADD DVT_PE GASTRDUO_ULCER GAST_DUODENITIS GI_BLEED HEP_CIRR_OTR_LIVER IBS INTEST_OBSTR MILD_SLEEP_APNEA NUTR_OTR_ANEMIA RESP_FAILURE RHEU_ARTH SCREEN_W_ADD SHOCK_SYNC STROKE_PARAL TOBACCO / SELECTION=BACKWARD SLS=0.15 ALPHA=0.1 ; title "Backward Selection Model"; run; quit;</CODE></PRE> <P>&nbsp;</P> <P>and got this report: I want to save this report to a sas data set in the same format. I used the option outset=estimate and did not get what I want. Do you have a way to do this? Thanks!</P> <DIV>Variable Parameter<BR />Estimate Standard<BR />Error Type&nbsp;II&nbsp;SS F Value Pr&nbsp;&gt;&nbsp;F <TABLE cellspacing="0" cellpadding="0"> <TBODY> <TR> <TD>Intercept</TD> <TD>7.05997</TD> <TD>0.00517</TD> <TD>151738</TD> <TD>1863176</TD> <TD>&lt;.0001</TD> </TR> <TR> <TD>ABDOM_HERNIA</TD> <TD>0.11768</TD> <TD>0.04140</TD> <TD>0.65785</TD> <TD>8.08</TD> <TD>0.0045</TD> </TR> <TR> <TD>ADV_DIABETES</TD> <TD>0.03687</TD> <TD>0.01479</TD> <TD>0.50618</TD> <TD>6.22</TD> <TD>0.0127</TD> </TR> <TR> <TD>CHF_CARDIOMYO_VALVDIS</TD> <TD>0.09931</TD> <TD>0.02582</TD> <TD>1.20509</TD> <TD>14.80</TD> <TD>0.0001</TD> </TR> <TR> <TD>CHRON_RENAL_FAIL</TD> <TD>0.11154</TD> <TD>0.04609</TD> <TD>0.47694</TD> <TD>5.86</TD> <TD>0.0155</TD> </TR> <TR> <TD>DEP_BIPOLAR_PARA</TD> <TD>0.09403</TD> <TD>0.02506</TD> <TD>1.14656</TD> <TD>14.08</TD> <TD>0.0002</TD> </TR> <TR> <TD>DIAG_W_ADD</TD> <TD>0.30107</TD> <TD>0.00906</TD> <TD>89.88892</TD> <TD>1103.74</TD> <TD>&lt;.0001</TD> </TR> <TR> <TD>DVT_PE</TD> <TD>0.05880</TD> <TD>0.03807</TD> <TD>0.19423</TD> <TD>2.38</TD> <TD>0.1225</TD> </TR> <TR> <TD>GASTRDUO_ULCER</TD> <TD>0.04103</TD> <TD>0.03024</TD> <TD>0.14988</TD> <TD>1.84</TD> <TD>0.1750</TD> </TR> <TR> <TD>GAST_DUODENITIS</TD> <TD>0.26914</TD> <TD>0.01104</TD> <TD>48.38799</TD> <TD>594.15</TD> <TD>&lt;.0001</TD> </TR> <TR> <TD>GI_BLEED</TD> <TD>0.08496</TD> <TD>0.01131</TD> <TD>4.59823</TD> <TD>56.46</TD> <TD>&lt;.0001</TD> </TR> <TR> <TD>HEP_CIRR_OTR_LIVER</TD> <TD>0.14005</TD> <TD>0.02110</TD> <TD>3.58960</TD> <TD>44.08</TD> <TD>&lt;.0001</TD> </TR> <TR> <TD>IBS</TD> <TD>0.11712</TD> <TD>0.01032</TD> <TD>10.49936</TD> <TD>128.92</TD> <TD>&lt;.0001</TD> </TR> <TR> <TD>INTEST_OBSTR</TD> <TD>0.08401</TD> <TD>0.01877</TD> <TD>1.63125</TD> <TD>20.03</TD> <TD>&lt;.0001</TD> </TR> <TR> <TD>MILD_SLEEP_APNEA</TD> <TD>0.04275</TD> <TD>0.01265</TD> <TD>0.92967</TD> <TD>11.42</TD> <TD>0.0007</TD> </TR> <TR> <TD>NUTR_OTR_ANEMIA</TD> <TD>0.14219</TD> <TD>0.01517</TD> <TD>7.15148</TD> <TD>87.81</TD> <TD>&lt;.0001</TD> </TR> <TR> <TD>RESP_FAILURE</TD> <TD>0.14960</TD> <TD>0.02995</TD> <TD>2.03182</TD> <TD>24.95</TD> <TD>&lt;.0001</TD> </TR> <TR> <TD>RHEU_ARTH</TD> <TD>0.02965</TD> <TD>0.01502</TD> <TD>0.31725</TD> <TD>3.90</TD> <TD>0.0485</TD> </TR> <TR> <TD>SCREEN_W_ADD</TD> <TD>0.24392</TD> <TD>0.00721</TD> <TD>93.13549</TD> <TD>1143.60</TD> <TD>&lt;.0001</TD> </TR> <TR> <TD>SHOCK_SYNC</TD> <TD>0.20405</TD> <TD>0.04136</TD> <TD>1.98179</TD> <TD>24.33</TD> <TD>&lt;.0001</TD> </TR> <TR> <TD>STROKE_PARAL</TD> <TD>0.07213</TD> <TD>0.04339</TD> <TD>0.22507</TD> <TD>2.76</TD> <TD>0.0965</TD> </TR> <TR> <TD>TOBACCO</TD> <TD>0.10960</TD> <TD>0.01568</TD> <TD>3.97830</TD> <TD>48.85</TD> <TD>&lt;.0001</TD> </TR> </TBODY> </TABLE> </DIV> Wed, 29 Mar 2017 19:55:10 GMT https://communities.sas.com/t5/SAS-Procedures/multiple-linear-regression/m-p/345520#M63518 zhuxiaoyan1 2017-03-29T19:55:10Z Re: multiple linear regression https://communities.sas.com/t5/SAS-Procedures/multiple-linear-regression/m-p/345522#M63519 <P>Have you tried the ODS table instead?</P> <P>&nbsp;</P> <P>See instructions here on how to find the name and save it. My guess is it would be called ParameterEstimates.</P> <P>&nbsp;</P> <P><A href="http://blogs.sas.com/content/iml/2017/01/09/ods-output-any-statistic.html" target="_blank">http://blogs.sas.com/content/iml/2017/01/09/ods-output-any-statistic.html</A></P> Wed, 29 Mar 2017 19:56:18 GMT https://communities.sas.com/t5/SAS-Procedures/multiple-linear-regression/m-p/345522#M63519 Reeza 2017-03-29T19:56:18Z