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43 changes: 26 additions & 17 deletions 10-MultipleRegression-FactorialDesigns.html
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<a href="Exp_design_fast_3_ex_new_contrasts.html">Practicum 4: Experimenteel design: krachtanalyse oefening 3</a>
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Expand Down Expand Up @@ -761,15 +770,15 @@ <h2><span class="header-section-number">4.1</span> Verwijderen van

Linear Hypotheses:
Estimate Std. Error t value Pr(&gt;|t|)
poison: II - I == 0 0.04686 0.01744 2.688 0.07355 .
poison: II - I == 0 0.04686 0.01744 2.688 0.07351 .
poison: III - I == 0 0.19964 0.01744 11.451 &lt; 0.001 ***
poison: III - II == 0 0.15278 0.01744 8.763 &lt; 0.001 ***
treat: B - A == 0 -0.16574 0.02013 -8.233 &lt; 0.001 ***
treat: C - A == 0 -0.05721 0.02013 -2.842 0.05086 .
treat: C - A == 0 -0.05721 0.02013 -2.842 0.05099 .
treat: D - A == 0 -0.13583 0.02013 -6.747 &lt; 0.001 ***
treat: C - B == 0 0.10853 0.02013 5.391 &lt; 0.001 ***
treat: D - B == 0 0.02991 0.02013 1.485 0.61545
treat: D - C == 0 -0.07862 0.02013 -3.905 0.00279 **
treat: D - B == 0 0.02991 0.02013 1.485 0.61546
treat: D - C == 0 -0.07862 0.02013 -3.905 0.00277 **
---
Signif. codes: 0 &#39;***&#39; 0.001 &#39;**&#39; 0.01 &#39;*&#39; 0.05 &#39;.&#39; 0.1 &#39; &#39; 1
(Adjusted p values reported -- single-step method)</code></pre>
Expand All @@ -782,21 +791,21 @@ <h2><span class="header-section-number">4.1</span> Verwijderen van

Fit: lm(formula = 1/time ~ poison + treat, data = rats)

Quantile = 2.85
Quantile = 2.8489
95% family-wise confidence level


Linear Hypotheses:
Estimate lwr upr
poison: II - I == 0 0.0468641 -0.0028260 0.0965542
poison: III - I == 0 0.1996425 0.1499524 0.2493326
poison: III - II == 0 0.1527784 0.1030883 0.2024685
treat: B - A == 0 -0.1657402 -0.2231174 -0.1083631
treat: C - A == 0 -0.0572135 -0.1145907 0.0001636
treat: D - A == 0 -0.1358338 -0.1932110 -0.0784566
treat: C - B == 0 0.1085267 0.0511495 0.1659039
treat: D - B == 0 0.0299064 -0.0274708 0.0872836
treat: D - C == 0 -0.0786203 -0.1359975 -0.0212431</code></pre>
poison: II - I == 0 0.0468641 -0.0028065 0.0965347
poison: III - I == 0 0.1996425 0.1499719 0.2493131
poison: III - II == 0 0.1527784 0.1031078 0.2024490
treat: B - A == 0 -0.1657402 -0.2230949 -0.1083856
treat: C - A == 0 -0.0572135 -0.1145682 0.0001411
treat: D - A == 0 -0.1358338 -0.1931885 -0.0784791
treat: C - B == 0 0.1085267 0.0511720 0.1658814
treat: D - B == 0 0.0299064 -0.0274483 0.0872611
treat: D - C == 0 -0.0786203 -0.1359750 -0.0212656</code></pre>
<div class="sourceCode" id="cb17"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb17-1"><a href="#cb17-1" aria-hidden="true" tabindex="-1"></a><span class="fu">plot</span>(comparisons,<span class="at">yaxt=</span><span class="st">&quot;none&quot;</span>)</span>
<span id="cb17-2"><a href="#cb17-2" aria-hidden="true" tabindex="-1"></a>contrastNames <span class="ot">&lt;-</span> <span class="fu">c</span>(<span class="st">&quot;II-I&quot;</span>,<span class="st">&quot;III-I&quot;</span>,<span class="st">&quot;III-II&quot;</span>,<span class="st">&quot;B-A&quot;</span>,<span class="st">&quot;C-A&quot;</span>,<span class="st">&quot;D-A&quot;</span>,<span class="st">&quot;C-B&quot;</span>,<span class="st">&quot;D-B&quot;</span>,<span class="st">&quot;D-C&quot;</span>)</span>
<span id="cb17-3"><a href="#cb17-3" aria-hidden="true" tabindex="-1"></a><span class="fu">axis</span>(<span class="dv">2</span>,<span class="at">at=</span><span class="fu">c</span>(<span class="fu">length</span>(contrastNames)<span class="sc">:</span><span class="dv">1</span>), <span class="at">labels=</span>contrastNames,<span class="at">las=</span><span class="dv">2</span>)</span></code></pre></div>
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<a href="Exp_design_fast_3_ex_new_contrasts.html">Practicum 4: Experimenteel design: krachtanalyse oefening 3</a>
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Expand Down Expand Up @@ -953,9 +962,9 @@ <h3><span class="header-section-number">4.1.2</span> Besluitvorming</h3>
##
## Linear Hypotheses:
## Estimate Std. Error t value Pr(&gt;|t|)
## Age == 0 0.43999 0.01511 29.127 &lt;1e-10 ***
## Age + Age:Gendermale == 0 0.24840 0.01879 13.217 &lt;1e-10 ***
## Age:Gendermale == 0 -0.19159 0.02411 -7.946 &lt;1e-10 ***
## Age == 0 0.43999 0.01511 29.127 &lt; 2e-16 ***
## Age + Age:Gendermale == 0 0.24840 0.01879 13.217 &lt; 2e-16 ***
## Age:Gendermale == 0 -0.19159 0.02411 -7.946 2.78e-15 ***
## ---
## Signif. codes: 0 &#39;***&#39; 0.001 &#39;**&#39; 0.01 &#39;*&#39; 0.05 &#39;.&#39; 0.1 &#39; &#39; 1
## (Adjusted p values reported -- single-step method)</code></pre>
Expand All @@ -966,26 +975,26 @@ <h3><span class="header-section-number">4.1.2</span> Besluitvorming</h3>
##
## Fit: lm(formula = BPSysAve ~ Age * Gender, data = bpData, weights = 1/mSd$fitted^2)
##
## Quantile = 2.3156
## Quantile = 2.3163
## 95% family-wise confidence level
##
##
## Linear Hypotheses:
## Estimate lwr upr
## Age == 0 0.4400 0.4050 0.4750
## Age + Age:Gendermale == 0 0.2484 0.2049 0.2919
## Age:Gendermale == 0 -0.1916 -0.2474 -0.1358</code></pre>
## Age:Gendermale == 0 -0.1916 -0.2474 -0.1357</code></pre>
</div>
<div id="conclusie" class="section level3" number="4.1.3">
<h3><span class="header-section-number">4.1.3</span> Conclusie</h3>
<p>We kunnen besluiten dat er een extreem significante associatie is
tussen leeftijd en de bloeddruk (p &lt;&lt; 0.001). De bloeddruk bij
twee vrouwen die in leeftijd verschillen is gemiddeld 0.44 mm Hg hoger
per jaar leeftijdsverschil bij de oudste vrouw en dat verschil is
extreem significant (p &lt;&lt; 0.001, 95% BI [0.41, 0.47]). De
bloeddruk bij mannen die in leeftijd verschillen is gemiddeld 0.25 mm Hg
hoger per jaar leeftijdsverschil bij de oudere man. (p &lt;&lt; 0.001,
95% BI [0.2, 0.29]). Het gemiddelde bloeddrukverschil tussen personen in
extreem significant (p &lt;&lt; 0.001, 95% BI [0.4, 0.47]). De bloeddruk
bij mannen die in leeftijd verschillen is gemiddeld 0.25 mm Hg hoger per
jaar leeftijdsverschil bij de oudere man. (p &lt;&lt; 0.001, 95% BI
[0.2, 0.29]). Het gemiddelde bloeddrukverschil tussen personen in
leeftijd verschillen is gemiddeld 0.19 mm Hg/jaar lager bij mannen dan
vrouwen (p &lt;&lt; 0.001, 95% BI [-0.25, -0.14]).</p>
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Expand Down Expand Up @@ -1410,7 +1419,7 @@ <h2><span class="header-section-number">5.3</span> Conclusie</h2>
class="math inline">\(^{-1}\)</span>, 95% BI III-II: [0.1, 0.2]h<span
class="math inline">\(^{-1}\)</span>) De gemiddelde snelheid van sterven
was niet significant verschillend tussen ratten die werden blootgesteld
aan gif I en gif II (p=0.073).</p>
aan gif I en gif II (p=0.074).</p>
<p>De snelheid van sterven is gemiddeld 0.17h<span
class="math inline">\(^{-1}\)</span> en 0.14h<span
class="math inline">\(^{-1}\)</span> hoger na behandeling A dan na
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Expand Down Expand Up @@ -802,9 +811,9 @@ <h1><span class="header-section-number">3</span> Hypotheses testen</h1>
##
## Linear Hypotheses:
## Estimate Std. Error t value Pr(&gt;|t|)
## bacon == 0 -1.19081 0.13182 -9.034 &lt;0.001 ***
## bacon + bacon:sexmale == 0 -0.87572 0.06286 -13.930 &lt;0.001 ***
## bacon:sexmale == 0 0.31509 0.14603 2.158 0.0736 .
## bacon == 0 -1.19081 0.13182 -9.034 &lt;1e-04 ***
## bacon + bacon:sexmale == 0 -0.87572 0.06286 -13.930 &lt;1e-04 ***
## bacon:sexmale == 0 0.31509 0.14603 2.158 0.0734 .
## ---
## Signif. codes: 0 &#39;***&#39; 0.001 &#39;**&#39; 0.01 &#39;*&#39; 0.05 &#39;.&#39; 0.1 &#39; &#39; 1
## (Adjusted p values reported -- single-step method)</code></pre>
Expand All @@ -815,15 +824,15 @@ <h1><span class="header-section-number">3</span> Hypotheses testen</h1>
##
## Fit: lm(formula = permeat ~ bacon + length + sex + bacon:sex, data = pigs)
##
## Quantile = 2.3188
## Quantile = 2.3176
## 95% family-wise confidence level
##
##
## Linear Hypotheses:
## Estimate lwr upr
## bacon == 0 -1.19081 -1.49648 -0.88515
## bacon + bacon:sexmale == 0 -0.87572 -1.02149 -0.72995
## bacon:sexmale == 0 0.31509 -0.02352 0.65370</code></pre>
## bacon == 0 -1.19081 -1.49632 -0.88530
## bacon + bacon:sexmale == 0 -0.87572 -1.02141 -0.73002
## bacon:sexmale == 0 0.31509 -0.02334 0.65353</code></pre>
</div>
<div id="conclusie" class="section level1" number="4">
<h1><span class="header-section-number">4</span> Conclusie</h1>
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