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    <title>topic Re: Cox proportional hazards in Discussions</title>
    <link>https://community.jmp.com/t5/Discussions/Cox-proportional-hazards/m-p/52562#M29759</link>
    <description>&lt;P&gt;Hi Jian&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Does Jmp pro 13.2 have the option for time-dependent or time-varying covariates. I tried to find some info but I could not.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Hope you can shed more light on my question&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Thank you&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Chris&lt;/P&gt;</description>
    <pubDate>Mon, 05 Mar 2018 00:32:56 GMT</pubDate>
    <dc:creator>triunk</dc:creator>
    <dc:date>2018-03-05T00:32:56Z</dc:date>
    <item>
      <title>Cox proportional hazards</title>
      <link>https://community.jmp.com/t5/Discussions/Cox-proportional-hazards/m-p/17472#M15929</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Hi!&lt;/P&gt;&lt;P&gt;I am very new to this forum and to JMP&amp;amp;statistics in general. I would appreciate if somebody could advise me on a following issue:&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;I am analyzing whether certain factors (A, B, C etc - all of them are continuous variables) are predictors of a disease (X) incidence. I have 2 independent groups of patients (group 1 - healthy, and group 2 - those ended up with a disease). I need to adjust those factors for age, gender, race etc. When I go to Analyze-&amp;gt;Reliability and Survival-&amp;gt;Fit Proportional hazards I am a little bit puzzled what goes where. Could you please advise?&lt;/P&gt;&lt;P&gt;I apologize those of you who will see this question as a very basic one. I was trying to look it up online but could not fins a definite answer anywhere &lt;SPAN __jive_emoticon_name="sad" __jive_macro_name="emoticon" class="jive_emote jive_macro" src="https://community.jmp.com/7.0.4.3b79b96/images/emoticons/sad.png"&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;I will greatly appreciate your help!&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Casandra&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Wed, 16 Mar 2016 03:25:25 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Cox-proportional-hazards/m-p/17472#M15929</guid>
      <dc:creator>matylda_m_inter</dc:creator>
      <dc:date>2016-03-16T03:25:25Z</dc:date>
    </item>
    <item>
      <title>Re: Cox proportional hazards</title>
      <link>https://community.jmp.com/t5/Discussions/Cox-proportional-hazards/m-p/17473#M15930</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;In this Mastering JMP WebEx, I showed how to fit a Cox's PH model to the data similar to yours. This is the link to the recordings: &lt;A href="http://www.jmp.com/en_us/events/ondemand/mastering-jmp/analyzing-survival-data.html" title="http://www.jmp.com/en_us/events/ondemand/mastering-jmp/analyzing-survival-data.html"&gt;Advanced Mastering JMP: Analyzing Survival Data | JMP&lt;/A&gt;&lt;/P&gt;&lt;P&gt;Hope it helps.&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Fri, 18 Mar 2016 16:20:04 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Cox-proportional-hazards/m-p/17473#M15930</guid>
      <dc:creator>jiancao</dc:creator>
      <dc:date>2016-03-18T16:20:04Z</dc:date>
    </item>
    <item>
      <title>Re: Cox proportional hazards</title>
      <link>https://community.jmp.com/t5/Discussions/Cox-proportional-hazards/m-p/17474#M15931</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;It may be that the proportional hazards is not the appropriate approach here. You should learn from the Mastering webex that this method is for when you have a time-to-event outcome, such as time-to-death. These methods also deal with censoring. For example, where you have subjects at the end of the observed time period who have still not experienced the event.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;It sounds like in your situation all you know about the outcome for the subject is a binary: healthy or with-disease (1 / 2). So this would be handled with a logistic regression.&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Thu, 24 Mar 2016 13:29:53 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Cox-proportional-hazards/m-p/17474#M15931</guid>
      <dc:creator>Phil_Kay</dc:creator>
      <dc:date>2016-03-24T13:29:53Z</dc:date>
    </item>
    <item>
      <title>Re: Cox proportional hazards</title>
      <link>https://community.jmp.com/t5/Discussions/Cox-proportional-hazards/m-p/52562#M29759</link>
      <description>&lt;P&gt;Hi Jian&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Does Jmp pro 13.2 have the option for time-dependent or time-varying covariates. I tried to find some info but I could not.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Hope you can shed more light on my question&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Thank you&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Chris&lt;/P&gt;</description>
      <pubDate>Mon, 05 Mar 2018 00:32:56 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Cox-proportional-hazards/m-p/52562#M29759</guid>
      <dc:creator>triunk</dc:creator>
      <dc:date>2018-03-05T00:32:56Z</dc:date>
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