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    <title>topic Modeling effect of fixed exposure in multiple time-windows in follow-up using PROC PHREG in SAS Procedures</title>
    <link>https://communities.sas.com/t5/SAS-Procedures/Modeling-effect-of-fixed-exposure-in-multiple-time-windows-in/m-p/162822#M42276</link>
    <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P class="p1"&gt;Hello everyone!&amp;nbsp; Thanks in advance for your help.&amp;nbsp; I'm looking for some guidance on how to program a model that I can't seem to find information on in my textbooks and in SAS documentation.&lt;/P&gt;&lt;P class="p1"&gt;&lt;/P&gt;&lt;P class="p1"&gt;&lt;SPAN style="font-size: 10pt; line-height: 1.5em;"&gt;I am conducting a cohort study in which I'm trying to model an outcome which can occur over 365 days of follow-up after exposure.&amp;nbsp; Due to changes in proportional hazards over follow-up, I want to seperately model the effect of exposure on the outcome (event) over three separate time intervals (0-14 days, 15-90 days, 90-365 days). Just to note - exposure status cannot actually change over time (this is why I think the standard time-varying covariate documentation doesn't apply to my question). Exposure status cannot change but I want to separately calculate effect estimates reflecting hazards 0-14 days after exposure, 15-90 days after exposure, and 90-365 days after exposure.&amp;nbsp; It also may be important to mention, no events can actually occur during the period 0-14 days (which is partially why I want to model that period separately).&lt;/SPAN&gt;&lt;/P&gt;&lt;P class="p1"&gt;&lt;/P&gt;&lt;P class="p1"&gt;In order to calculate independent hazard ratios for these different time periods, I want to use dummy variables.&amp;nbsp; I've attempted to code them as follows:&lt;/P&gt;&lt;P class="p4"&gt;&lt;SPAN class="s1"&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; IF&lt;/SPAN&gt; time GT &lt;SPAN class="s2"&gt;&lt;STRONG&gt;14&lt;/STRONG&gt;&lt;/SPAN&gt; AND time LE &lt;SPAN class="s2"&gt;&lt;STRONG&gt;90&lt;/STRONG&gt;&lt;/SPAN&gt; &lt;SPAN class="s1"&gt;THEN&lt;/SPAN&gt; time_dummy1=&lt;SPAN class="s2"&gt;&lt;STRONG&gt;1&lt;/STRONG&gt;&lt;/SPAN&gt;;&lt;/P&gt;&lt;P class="p4"&gt;&lt;SPAN class="s1"&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; ELSE&lt;/SPAN&gt; time_dummy1=&lt;SPAN class="s2"&gt;&lt;STRONG&gt;0&lt;/STRONG&gt;&lt;/SPAN&gt;;&lt;/P&gt;&lt;P class="p4"&gt;&lt;SPAN class="s1"&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; IF&lt;/SPAN&gt; time GT &lt;SPAN class="s2"&gt;&lt;STRONG&gt;90&lt;/STRONG&gt;&lt;/SPAN&gt; &lt;SPAN class="s1"&gt;THEN&lt;/SPAN&gt; time_dummy2=&lt;SPAN class="s2"&gt;&lt;STRONG&gt;1&lt;/STRONG&gt;&lt;/SPAN&gt;;&lt;/P&gt;&lt;P class="p4"&gt;&lt;SPAN class="s1"&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; ELSE&lt;/SPAN&gt; time_dummy2=&lt;SPAN class="s2"&gt;&lt;STRONG&gt;0&lt;/STRONG&gt;&lt;/SPAN&gt;;&lt;/P&gt;&lt;P class="p5"&gt;&lt;/P&gt;&lt;P class="p1"&gt;&lt;EM&gt;&lt;STRONG&gt;Time&lt;/STRONG&gt; refers to the amount of time spent in the cohort by each subject.&amp;nbsp; For people with events or who lose eligibility during follow-up, &lt;STRONG&gt;time&lt;/STRONG&gt; &amp;lt; 365.&amp;nbsp; For the vast majority who experienced no event and were not censored, &lt;STRONG&gt;time&lt;/STRONG&gt; = 365.&lt;/EM&gt;&lt;/P&gt;&lt;P class="p2"&gt;&lt;/P&gt;&lt;P class="p1"&gt;Next, I used the following PROC PHREG code to calculate parameter estimates:&lt;/P&gt;&lt;P class="p4"&gt;&lt;SPAN class="s3"&gt;&lt;STRONG&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; proc&lt;/STRONG&gt;&lt;/SPAN&gt; &lt;SPAN class="s3"&gt;&lt;STRONG&gt;phreg&lt;/STRONG&gt;&lt;/SPAN&gt; &lt;SPAN class="s1"&gt;data&lt;/SPAN&gt;=CollapsedFlags;&lt;/P&gt;&lt;P class="p4"&gt;&lt;SPAN class="s1"&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; MODEL&lt;/SPAN&gt; time*event(&lt;SPAN class="s2"&gt;&lt;STRONG&gt;0&lt;/STRONG&gt;&lt;/SPAN&gt;) = exposure &lt;SPAN style="font-size: 10pt; line-height: 1.5em;"&gt;exposure*time_dummy1 exposure*time_dummy2 &lt;/SPAN&gt;&lt;SPAN style="font-size: 10pt; line-height: 1.5em;"&gt;/ &lt;/SPAN&gt;&lt;SPAN class="s1" style="font-size: 10pt; line-height: 1.5em;"&gt;rl&lt;/SPAN&gt;&lt;SPAN style="font-size: 10pt; line-height: 1.5em;"&gt;;&lt;/SPAN&gt;&lt;/P&gt;&lt;P class="p7"&gt;&lt;STRONG&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; RUN&lt;/STRONG&gt;&lt;SPAN class="s4"&gt;;&lt;/SPAN&gt;&lt;/P&gt;&lt;P class="p8"&gt;&lt;/P&gt;&lt;P&gt;The problem is for the exposure&lt;EM&gt;*&lt;/EM&gt;time_dummy2 interaction, I get no parameter estimate (or standard error). &lt;SPAN style="font-size: 10pt; line-height: 1.5em;"&gt;I assumed the output would allow me to calculate the HR for the second time period by combining the parameter estimates for exposure and exposure*time_dummy1 and for the third time period by combining the estimates for exposure and exposure*time_dummy 2.&amp;nbsp; Wouldn't these results (exposure*time_dummy2 estime = 0) imply that the hazard in time period 3 is the same as the hazard in time period 1?&amp;nbsp; Am I miscoding this?&amp;nbsp; Any guidance (or recommendations for references) would be helpful and appreciated.&lt;/SPAN&gt;&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
    <pubDate>Fri, 16 May 2014 20:37:16 GMT</pubDate>
    <dc:creator>mconover</dc:creator>
    <dc:date>2014-05-16T20:37:16Z</dc:date>
    <item>
      <title>Modeling effect of fixed exposure in multiple time-windows in follow-up using PROC PHREG</title>
      <link>https://communities.sas.com/t5/SAS-Procedures/Modeling-effect-of-fixed-exposure-in-multiple-time-windows-in/m-p/162822#M42276</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P class="p1"&gt;Hello everyone!&amp;nbsp; Thanks in advance for your help.&amp;nbsp; I'm looking for some guidance on how to program a model that I can't seem to find information on in my textbooks and in SAS documentation.&lt;/P&gt;&lt;P class="p1"&gt;&lt;/P&gt;&lt;P class="p1"&gt;&lt;SPAN style="font-size: 10pt; line-height: 1.5em;"&gt;I am conducting a cohort study in which I'm trying to model an outcome which can occur over 365 days of follow-up after exposure.&amp;nbsp; Due to changes in proportional hazards over follow-up, I want to seperately model the effect of exposure on the outcome (event) over three separate time intervals (0-14 days, 15-90 days, 90-365 days). Just to note - exposure status cannot actually change over time (this is why I think the standard time-varying covariate documentation doesn't apply to my question). Exposure status cannot change but I want to separately calculate effect estimates reflecting hazards 0-14 days after exposure, 15-90 days after exposure, and 90-365 days after exposure.&amp;nbsp; It also may be important to mention, no events can actually occur during the period 0-14 days (which is partially why I want to model that period separately).&lt;/SPAN&gt;&lt;/P&gt;&lt;P class="p1"&gt;&lt;/P&gt;&lt;P class="p1"&gt;In order to calculate independent hazard ratios for these different time periods, I want to use dummy variables.&amp;nbsp; I've attempted to code them as follows:&lt;/P&gt;&lt;P class="p4"&gt;&lt;SPAN class="s1"&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; IF&lt;/SPAN&gt; time GT &lt;SPAN class="s2"&gt;&lt;STRONG&gt;14&lt;/STRONG&gt;&lt;/SPAN&gt; AND time LE &lt;SPAN class="s2"&gt;&lt;STRONG&gt;90&lt;/STRONG&gt;&lt;/SPAN&gt; &lt;SPAN class="s1"&gt;THEN&lt;/SPAN&gt; time_dummy1=&lt;SPAN class="s2"&gt;&lt;STRONG&gt;1&lt;/STRONG&gt;&lt;/SPAN&gt;;&lt;/P&gt;&lt;P class="p4"&gt;&lt;SPAN class="s1"&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; ELSE&lt;/SPAN&gt; time_dummy1=&lt;SPAN class="s2"&gt;&lt;STRONG&gt;0&lt;/STRONG&gt;&lt;/SPAN&gt;;&lt;/P&gt;&lt;P class="p4"&gt;&lt;SPAN class="s1"&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; IF&lt;/SPAN&gt; time GT &lt;SPAN class="s2"&gt;&lt;STRONG&gt;90&lt;/STRONG&gt;&lt;/SPAN&gt; &lt;SPAN class="s1"&gt;THEN&lt;/SPAN&gt; time_dummy2=&lt;SPAN class="s2"&gt;&lt;STRONG&gt;1&lt;/STRONG&gt;&lt;/SPAN&gt;;&lt;/P&gt;&lt;P class="p4"&gt;&lt;SPAN class="s1"&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; ELSE&lt;/SPAN&gt; time_dummy2=&lt;SPAN class="s2"&gt;&lt;STRONG&gt;0&lt;/STRONG&gt;&lt;/SPAN&gt;;&lt;/P&gt;&lt;P class="p5"&gt;&lt;/P&gt;&lt;P class="p1"&gt;&lt;EM&gt;&lt;STRONG&gt;Time&lt;/STRONG&gt; refers to the amount of time spent in the cohort by each subject.&amp;nbsp; For people with events or who lose eligibility during follow-up, &lt;STRONG&gt;time&lt;/STRONG&gt; &amp;lt; 365.&amp;nbsp; For the vast majority who experienced no event and were not censored, &lt;STRONG&gt;time&lt;/STRONG&gt; = 365.&lt;/EM&gt;&lt;/P&gt;&lt;P class="p2"&gt;&lt;/P&gt;&lt;P class="p1"&gt;Next, I used the following PROC PHREG code to calculate parameter estimates:&lt;/P&gt;&lt;P class="p4"&gt;&lt;SPAN class="s3"&gt;&lt;STRONG&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; proc&lt;/STRONG&gt;&lt;/SPAN&gt; &lt;SPAN class="s3"&gt;&lt;STRONG&gt;phreg&lt;/STRONG&gt;&lt;/SPAN&gt; &lt;SPAN class="s1"&gt;data&lt;/SPAN&gt;=CollapsedFlags;&lt;/P&gt;&lt;P class="p4"&gt;&lt;SPAN class="s1"&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; MODEL&lt;/SPAN&gt; time*event(&lt;SPAN class="s2"&gt;&lt;STRONG&gt;0&lt;/STRONG&gt;&lt;/SPAN&gt;) = exposure &lt;SPAN style="font-size: 10pt; line-height: 1.5em;"&gt;exposure*time_dummy1 exposure*time_dummy2 &lt;/SPAN&gt;&lt;SPAN style="font-size: 10pt; line-height: 1.5em;"&gt;/ &lt;/SPAN&gt;&lt;SPAN class="s1" style="font-size: 10pt; line-height: 1.5em;"&gt;rl&lt;/SPAN&gt;&lt;SPAN style="font-size: 10pt; line-height: 1.5em;"&gt;;&lt;/SPAN&gt;&lt;/P&gt;&lt;P class="p7"&gt;&lt;STRONG&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; RUN&lt;/STRONG&gt;&lt;SPAN class="s4"&gt;;&lt;/SPAN&gt;&lt;/P&gt;&lt;P class="p8"&gt;&lt;/P&gt;&lt;P&gt;The problem is for the exposure&lt;EM&gt;*&lt;/EM&gt;time_dummy2 interaction, I get no parameter estimate (or standard error). &lt;SPAN style="font-size: 10pt; line-height: 1.5em;"&gt;I assumed the output would allow me to calculate the HR for the second time period by combining the parameter estimates for exposure and exposure*time_dummy1 and for the third time period by combining the estimates for exposure and exposure*time_dummy 2.&amp;nbsp; Wouldn't these results (exposure*time_dummy2 estime = 0) imply that the hazard in time period 3 is the same as the hazard in time period 1?&amp;nbsp; Am I miscoding this?&amp;nbsp; Any guidance (or recommendations for references) would be helpful and appreciated.&lt;/SPAN&gt;&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Fri, 16 May 2014 20:37:16 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Procedures/Modeling-effect-of-fixed-exposure-in-multiple-time-windows-in/m-p/162822#M42276</guid>
      <dc:creator>mconover</dc:creator>
      <dc:date>2014-05-16T20:37:16Z</dc:date>
    </item>
    <item>
      <title>Re: Modeling effect of fixed exposure in multiple time-windows in follow-up using PROC PHREG</title>
      <link>https://communities.sas.com/t5/SAS-Procedures/Modeling-effect-of-fixed-exposure-in-multiple-time-windows-in/m-p/162823#M42277</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;First of all, thanks to everyone who spent time reviewing this question.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Not sure I have a complete handle on this issue yet but wanted to share what I've learned over the weekend.&amp;nbsp; I found some illuminating information in a textbook of mine on time-varying covariates (even though this covariate doesn't vary over time - it's effect potentially does).&amp;nbsp; On page 154 of Survival Analysis using SAS: A Practical Guide (2nd edition), Paul D. Allison&amp;nbsp; describes the two methods PROC PHREG can use to deal with time-dependant covariates: 1) counting process method and 2) programming statements method.&amp;nbsp; &lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;In the counting process method, the dataset being analyzed has numerous observations per subject, each observation referring to a time-period over which time-varying covariates remained constant. The programming statements method considers a summary dataset with one observation per subject which contains numerous variables which&amp;nbsp; refer to variable values for time-varying confounders.&amp;nbsp; The programming statements method requires that the programming that generates the time-dependant covariates must be a part of every PROC PHREG run.&amp;nbsp; As a result, the time-varying covariates must be coded within the actual PROC PHREG step.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Still trying to figure out exactly why and how this is working but I'm pretty sure now that I've incorporated my time-variable coding into PROC PHREG I'm getting the correct estimates.&amp;nbsp; Please refer to the Hazard Ratios (&amp;amp; associated standard errors) below.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P class="p1"&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; Contrast Estimation and Testing Results by Row&lt;/P&gt;&lt;P class="p1"&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; &lt;/P&gt;&lt;P class="p1"&gt; &lt;SPAN style="text-decoration: underline;"&gt;Contrast&lt;/SPAN&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; &lt;SPAN style="text-decoration: underline;"&gt;Type&lt;/SPAN&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; &lt;SPAN style="text-decoration: underline;"&gt;Estimate&lt;/SPAN&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; &lt;SPAN style="text-decoration: underline;"&gt;SE&lt;/SPAN&gt;&lt;/P&gt;&lt;P class="p1"&gt; Exposure: time 0 to 14&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; EXP&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 0.00006&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 0.01&lt;/P&gt;&lt;P class="p1"&gt; Exposure: time 14 to 180&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; EXP&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 0.20&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 0.15&lt;/P&gt;&lt;P class="p1"&gt; Exposure: time 180 to 365&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; EXP&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 0.85&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 0.09&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Mon, 19 May 2014 14:28:10 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Procedures/Modeling-effect-of-fixed-exposure-in-multiple-time-windows-in/m-p/162823#M42277</guid>
      <dc:creator>mconover</dc:creator>
      <dc:date>2014-05-19T14:28:10Z</dc:date>
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