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    <title>topic Re: Multiple regression with dummy variables in Discussions</title>
    <link>https://community.jmp.com/t5/Discussions/Multiple-regression-with-dummy-variables/m-p/634451#M83238</link>
    <description>&lt;P&gt;This post describes how to use the Fit Y-by-X/Bivariate platform with by()&amp;nbsp; .... to collect the slopes and intercepts:&lt;/P&gt;&lt;P&gt;&lt;A href="https://community.jmp.com/t5/Discussions/Creating-columns-from-Linear-Fit-Constants-slope-intercept/m-p/254247/highlight/true#M49911" target="_blank" rel="noopener"&gt;Creating-columns-from-Linear-Fit-Constants-slope-intercept&lt;/A&gt;&amp;nbsp;&lt;/P&gt;</description>
    <pubDate>Wed, 24 May 2023 05:39:19 GMT</pubDate>
    <dc:creator>hogi</dc:creator>
    <dc:date>2023-05-24T05:39:19Z</dc:date>
    <item>
      <title>Multiple regression with dummy variables</title>
      <link>https://community.jmp.com/t5/Discussions/Multiple-regression-with-dummy-variables/m-p/634269#M83225</link>
      <description>&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;How can I select intercept in multiple regression?&lt;/P&gt;&lt;P&gt;I want two lines to cross the Y axis in the (0,100) point.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Thanks&lt;/P&gt;&lt;P&gt;Tohar&lt;/P&gt;</description>
      <pubDate>Tue, 23 May 2023 10:50:25 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Multiple-regression-with-dummy-variables/m-p/634269#M83225</guid>
      <dc:creator>Tohar</dc:creator>
      <dc:date>2023-05-23T10:50:25Z</dc:date>
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    <item>
      <title>Re: Multiple regression with dummy variables</title>
      <link>https://community.jmp.com/t5/Discussions/Multiple-regression-with-dummy-variables/m-p/634374#M83233</link>
      <description>&lt;P&gt;I assume that you selected Analyze &amp;gt; Fit Model to start the multiple regression. A check box is at the center of the bottom of the launch dialog. Select it to remove the intercept from the model&lt;/P&gt;</description>
      <pubDate>Tue, 23 May 2023 14:21:16 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Multiple-regression-with-dummy-variables/m-p/634374#M83233</guid>
      <dc:creator>Mark_Bailey</dc:creator>
      <dc:date>2023-05-23T14:21:16Z</dc:date>
    </item>
    <item>
      <title>Re: Multiple regression with dummy variables</title>
      <link>https://community.jmp.com/t5/Discussions/Multiple-regression-with-dummy-variables/m-p/634451#M83238</link>
      <description>&lt;P&gt;This post describes how to use the Fit Y-by-X/Bivariate platform with by()&amp;nbsp; .... to collect the slopes and intercepts:&lt;/P&gt;&lt;P&gt;&lt;A href="https://community.jmp.com/t5/Discussions/Creating-columns-from-Linear-Fit-Constants-slope-intercept/m-p/254247/highlight/true#M49911" target="_blank" rel="noopener"&gt;Creating-columns-from-Linear-Fit-Constants-slope-intercept&lt;/A&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Wed, 24 May 2023 05:39:19 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Multiple-regression-with-dummy-variables/m-p/634451#M83238</guid>
      <dc:creator>hogi</dc:creator>
      <dc:date>2023-05-24T05:39:19Z</dc:date>
    </item>
    <item>
      <title>Re: Multiple regression with dummy variables</title>
      <link>https://community.jmp.com/t5/Discussions/Multiple-regression-with-dummy-variables/m-p/634664#M83271</link>
      <description>&lt;P&gt;Perhaps more details are needed as I am the third to respond and I have a different take on your question. You said you wanted the lines to go through (0, 100). That is not the same as having the y-intercept of zero. You could use the nonlinear platform to build a model with a fixed y-intercept of 100 and the rest of the linear model to estimate the parameters with that restriction.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Provide a bit more clarity of your situation so that we can better assist you.&lt;/P&gt;</description>
      <pubDate>Tue, 23 May 2023 23:32:12 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Multiple-regression-with-dummy-variables/m-p/634664#M83271</guid>
      <dc:creator>Dan_Obermiller</dc:creator>
      <dc:date>2023-05-23T23:32:12Z</dc:date>
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      <title>Re: Multiple regression with dummy variables</title>
      <link>https://community.jmp.com/t5/Discussions/Multiple-regression-with-dummy-variables/m-p/634706#M83274</link>
      <description>&lt;P&gt;Oh, thanks, I miss-read this sentence.&lt;BR /&gt;In the Fit Y - by - X / Bivariate Platform there is also an option to set the intercept to a fixed value:&lt;BR /&gt;&lt;STRONG&gt;Constrain intercept to&lt;/STRONG&gt;&lt;/P&gt;&lt;P&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="hogi_1-1684906642116.png" style="width: 400px;"&gt;&lt;img src="https://community.jmp.com/t5/image/serverpage/image-id/53034i1C478918DCB8C9D3/image-size/medium?v=v2&amp;amp;px=400" role="button" title="hogi_1-1684906642116.png" alt="hogi_1-1684906642116.png" /&gt;&lt;/span&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="hogi_0-1684906555219.png" style="width: 400px;"&gt;&lt;img src="https://community.jmp.com/t5/image/serverpage/image-id/53033i7269549180459AAD/image-size/medium?v=v2&amp;amp;px=400" role="button" title="hogi_0-1684906555219.png" alt="hogi_0-1684906555219.png" /&gt;&lt;/span&gt;&lt;/P&gt;</description>
      <pubDate>Wed, 24 May 2023 05:38:52 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Multiple-regression-with-dummy-variables/m-p/634706#M83274</guid>
      <dc:creator>hogi</dc:creator>
      <dc:date>2023-05-24T05:38:52Z</dc:date>
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      <title>Re: Multiple regression with dummy variables</title>
      <link>https://community.jmp.com/t5/Discussions/Multiple-regression-with-dummy-variables/m-p/634813#M83288</link>
      <description>&lt;DIV class=""&gt;&lt;DIV class=""&gt;&lt;DIV&gt;&lt;DIV class=""&gt;&lt;SPAN class=""&gt;&lt;SPAN class=""&gt;I'm trying to do a multivariable linear regression.&lt;/SPAN&gt;&lt;/SPAN&gt; &lt;SPAN class=""&gt;&lt;SPAN class=""&gt;A continuous variable explains -X and a continuous variable is explained -Y and another dummy factor is categorical 0 or 1. I know that the lines should cut the Y-axis at 100 and I want to define this in the model.&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/DIV&gt;&lt;DIV class=""&gt;&lt;SPAN class=""&gt;&lt;SPAN class=""&gt;&amp;nbsp;Similar to the solution in the Fit Y by X platform that "hogi" suggested but I have two lines- two groups.&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/DIV&gt;&lt;DIV class=""&gt;&lt;SPAN class=""&gt;&lt;SPAN class=""&gt;Thank you very much&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/DIV&gt;&lt;DIV class=""&gt;&amp;nbsp;&lt;/DIV&gt;&lt;DIV class=""&gt;&amp;nbsp;&lt;/DIV&gt;&lt;/DIV&gt;&lt;/DIV&gt;&lt;/DIV&gt;</description>
      <pubDate>Wed, 24 May 2023 12:11:53 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Multiple-regression-with-dummy-variables/m-p/634813#M83288</guid>
      <dc:creator>Tohar</dc:creator>
      <dc:date>2023-05-24T12:11:53Z</dc:date>
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    <item>
      <title>Re: Multiple regression with dummy variables</title>
      <link>https://community.jmp.com/t5/Discussions/Multiple-regression-with-dummy-variables/m-p/634931#M83301</link>
      <description>&lt;P&gt;&lt;a href="https://community.jmp.com/t5/user/viewprofilepage/user-id/48027"&gt;@Tohar&lt;/a&gt;&amp;nbsp;, so it sounds like you have an ANCOVA model (one categorical factor C, and one continuous X) and you want to regress Y on these.&amp;nbsp; Define Y100 = Y-100.&amp;nbsp; then use Y100 as your response. then the only effect in your model will be C*X, with no intercept. See pic below. Also, in the red triangle pull down menu deselect "Center Polynomials".&amp;nbsp;&lt;/P&gt;&lt;P&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="MRB3855_0-1684938574310.png" style="width: 400px;"&gt;&lt;img src="https://community.jmp.com/t5/image/serverpage/image-id/53054iA6B0DD1FD9E39640/image-size/medium?v=v2&amp;amp;px=400" role="button" title="MRB3855_0-1684938574310.png" alt="MRB3855_0-1684938574310.png" /&gt;&lt;/span&gt;&lt;/P&gt;&lt;P&gt;Run this and get the following: And remember Y100 is Y-100. So, when Y100=0, Y=100. You can then get creative with Save Prediction Formula/Graph Builder/etc to get the Y axis back to the raw scale (shift it back up by 100).&lt;/P&gt;&lt;P&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="MRB3855_1-1684938625005.png" style="width: 400px;"&gt;&lt;img src="https://community.jmp.com/t5/image/serverpage/image-id/53055i9922128DCEB87F39/image-size/medium?v=v2&amp;amp;px=400" role="button" title="MRB3855_1-1684938625005.png" alt="MRB3855_1-1684938625005.png" /&gt;&lt;/span&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Wed, 24 May 2023 15:13:26 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Multiple-regression-with-dummy-variables/m-p/634931#M83301</guid>
      <dc:creator>MRB3855</dc:creator>
      <dc:date>2023-05-24T15:13:26Z</dc:date>
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    <item>
      <title>Re: Multiple regression with dummy variables</title>
      <link>https://community.jmp.com/t5/Discussions/Multiple-regression-with-dummy-variables/m-p/635030#M83319</link>
      <description>&lt;P&gt;Thank you very much&lt;/P&gt;&lt;P&gt;I am not about the result I got; the lines cross the Y axis in (0,0) - see attached.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;My goal is to check if there is a difference in rate (ie slope) between the two treatment groups.&amp;nbsp;It is not necessary to check whether there is a difference in the intercept, I want to set it both in the model and in the presentation graph at (0,100).&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Many thanks!!!!!&lt;/P&gt;&lt;P&gt;Tohar&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Wed, 24 May 2023 18:16:40 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Multiple-regression-with-dummy-variables/m-p/635030#M83319</guid>
      <dc:creator>Tohar</dc:creator>
      <dc:date>2023-05-24T18:16:40Z</dc:date>
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      <title>Re: Multiple regression with dummy variables</title>
      <link>https://community.jmp.com/t5/Discussions/Multiple-regression-with-dummy-variables/m-p/635038#M83321</link>
      <description>&lt;P&gt;&lt;a href="https://community.jmp.com/t5/user/viewprofilepage/user-id/48027"&gt;@Tohar&lt;/a&gt;&amp;nbsp; Assuming your model is correct (I have my doubts from looking at your residual plots etc),&amp;nbsp; the p-value for the parameter estimate and/or in the ANOVA table tells the story (they are equivalent)&amp;nbsp; If less than 0.05 (that is the "usual" threshold /Type 1 error rate) then you could claim that there is a difference in slope. Strictly speaking, you are testing whether or not there is any difference from the reduced model Y100=0 (i.e, just noise). The p-value says reject the Y100= 0 model in favor of the two slope model (where slope1 = - slope2).&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Wed, 24 May 2023 18:39:47 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Multiple-regression-with-dummy-variables/m-p/635038#M83321</guid>
      <dc:creator>MRB3855</dc:creator>
      <dc:date>2023-05-24T18:39:47Z</dc:date>
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    <item>
      <title>Re: Multiple regression with dummy variables</title>
      <link>https://community.jmp.com/t5/Discussions/Multiple-regression-with-dummy-variables/m-p/635050#M83324</link>
      <description>&lt;P&gt;Did you try the Group By command in the platform menu (red triangle) before using Fit Special and specifying a Y-intercept = 100?&lt;/P&gt;</description>
      <pubDate>Wed, 24 May 2023 18:53:07 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Multiple-regression-with-dummy-variables/m-p/635050#M83324</guid>
      <dc:creator>Mark_Bailey</dc:creator>
      <dc:date>2023-05-24T18:53:07Z</dc:date>
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      <title>Re: Multiple regression with dummy variables</title>
      <link>https://community.jmp.com/t5/Discussions/Multiple-regression-with-dummy-variables/m-p/635068#M83327</link>
      <description>&lt;P&gt;&lt;a href="https://community.jmp.com/t5/user/viewprofilepage/user-id/48027"&gt;@Tohar&lt;/a&gt;&amp;nbsp;. On second thought, use the same model with the interaction (as I said) and Days From Start.(see below). Then assess the equivalence of slopes via the p-value for the interaction parameter estimate. Adding the extra term will give more flexibility wrt the slope estimates (doesn't force slope1 = -slope2).&lt;/P&gt;&lt;P&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="MRB3855_0-1684954403611.png" style="width: 400px;"&gt;&lt;img src="https://community.jmp.com/t5/image/serverpage/image-id/53067iC75957CD3A074AC6/image-size/medium?v=v2&amp;amp;px=400" role="button" title="MRB3855_0-1684954403611.png" alt="MRB3855_0-1684954403611.png" /&gt;&lt;/span&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Wed, 24 May 2023 19:40:38 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Multiple-regression-with-dummy-variables/m-p/635068#M83327</guid>
      <dc:creator>MRB3855</dc:creator>
      <dc:date>2023-05-24T19:40:38Z</dc:date>
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      <title>Re: Multiple regression with dummy variables</title>
      <link>https://community.jmp.com/t5/Discussions/Multiple-regression-with-dummy-variables/m-p/635326#M83349</link>
      <description>&lt;P&gt;&lt;a href="https://community.jmp.com/t5/user/viewprofilepage/user-id/48027"&gt;@Tohar&lt;/a&gt;&amp;nbsp; For some more detail re my previous post.&amp;nbsp; Notice that I regressed Y-100 on T and T*ARM with no intercept.&lt;/P&gt;&lt;P&gt;So, the final equation is Y-100 = B0*T +&amp;nbsp; B1*T*I(ARM=C) + B2*T*I(ARM=S), where I(ARM=C) = 1 if ARM=C, 0 otherwise. I(ARM=S) is defined similarly. So, B1 and B2 are deviations from the overall mean slope (B0). Defined this way, the slope for ARM C = B0+B1, and the slope for ARM S = B0+B2. And, to see the common intercept is 100, add 100 to both sides of the equation to get.&lt;/P&gt;&lt;P&gt;Y = 100 + B0*T +&amp;nbsp; B1*T*I(ARM=C) + B2*T*I(ARM=S).&lt;/P&gt;</description>
      <pubDate>Thu, 25 May 2023 08:10:59 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Multiple-regression-with-dummy-variables/m-p/635326#M83349</guid>
      <dc:creator>MRB3855</dc:creator>
      <dc:date>2023-05-25T08:10:59Z</dc:date>
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