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2,821 バイト追加 、 2023年9月25日 (月) 19:48
{{Floating_Menu}} ==Basic concept of statistical tests==*First remind that**Statistical test is to test ==Comparing Proportions==
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!style="width:80px"|!style="width:200px250px"|Independent samples<br>(Unpaired in case of two)!style="width:200px250px"|Dependent samples<br>(Paired in case of two)
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 !style="width:40px"|2 proportions
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*'''Z test'''
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==Comparing Means==
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!rowspan="2" style="width:80px"|comparisons
!colspan="2"|Parametric<br>i.e., normally distributed
!colspan="2"|Non-parametric<br>i.e., not normally distributed
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!style="width:200px250px"|Independent samples<br>(Unpaired in case of two)!style="width:200px250px"|Dependent samples<br>(Paired in case of two)!style="width:200px250px"|Independent samples<br>(Unpaired in case of two)!style="width:200px250px"|Dependent samples<br>(Paired in case of two)
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!rowspan="3" style="width:40px"|2 means |''Enough large sample''
*'''Z test'''
::<math>
\end{align}
</math>
 
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*'''Paired Student's t test'''
::''<math>H_0</math> is '''mean of paired differences''' in the population is '''zero'''.''
::<math>
\begin{align}
</math>
::where <math>\bar{d}</math> is the mean of differences of paired observations
 
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*'''Wilcoxon rank sum test'''**AKA <br>='''Mann-Whitney test'''::''<math>H_0</math> is '''medians or means of ranks''' in the two population'''s''' are the same'':#To rank whole combined observations of two groups:#To separate back the ranks into two groups:#To look up ''critical range'' relevant to both numbers of observations and whether '''the sum of ranks''' in '''the group of smaller number of observation''' (=statistics) is outside the range or not::if outside the range, p-value is smaller than designated 
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*'''Wilcoxon signed rank test'''
**here ::''<math>H_0</math> is '''median of paired differences''' in the population is zero'':#To calculate differences between pairs and discard 0 differences:#To rank the absolute values of differences (ignoring 0):#To make the sum of ranks of '''positive difference''' and the sum of ranks of '''negative differences''' ('signedrank'):#To look up '''critical value' means 'take into account signs ' relevant to numbers of pairs with non-0 differences and whether '''the smaller sum of paired datarank'''(=statistics) is smaller than the critical value::if smaller than the critical value, p-value is smaller than designated 
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|''Small sample size <30 in a group''
\end{align}
</math>
 
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|''Large discrepancy in SDs between groups''
*Fisher-Behrens
*Welch
 
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!&ge; 3 means
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*'''One-way ANOVA'''::<math>\begin{align}F & = \frac{ \sum_{j=1}^k \sum_{j=1}^{n_j} (x_{ij}-\bar{x_j})^2 }{ k-1 } \\& \div \frac{ \sum_{j=1}^k (\bar{x_j}-\bar{x})^2 }{ n-k }\end{align}</math>::<math>n</math> is sample size (whole combined number of observations)::<math>k</math> is number of groups <!--::The variance of whole combined observations is ::<math>s^2=\frac{\sum_{i=1}^n (x_i-\bar{x})^2}{n-1}</math>::The numarator is ''sum of square''::<math>\sum_{i=1}^n (x_i-\bar{x})^2</math>::<math>= \sum_{i=1}^n x_i^2 - 2\bar{x} \sum_{i=1}^n x_i + \bar{x}^2 \sum_{i=1}^n 1</math>--> 
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*'''Linear-regression model'''
*Repeated measures ANOVA
 
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*'''Kruskall-Wallis test'''
::''<math>H_0</math> is '''medians or means of ranks''' in the all population'''s''' are the same''
:#To rank whole combined observations of all groups
:#To separate back the ranks into original groups
:#To make sum of ranks in each group
::<math>H = \frac{n-1}{n} \sum_{i=1}^k \frac{n_i(\bar{R}-E_R)}{s^2}</math>
::<math>H</math> is Kruskal-Wallis statistics
::<math>n_i</math> is number of observations in group <math>i</math>
::<math>\bar{R}</math> is the mean of rank sum in group <math>i</math>
::<math>E_R</math> is expected value of the rankings
::<math>s^2</math> is the variance of rank
::To look up ''critical values'' relevant to '''sum of ranks''' in '''the group of smaller number of observation'''
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*<nowiki>*</nowiki>''needs try to transform data into parametric (e.g., logarithmic), or other considerations''|} ==Comparing Survival time=={|class="wikitable"|-!style="width:50%"|Life table!style="width:50%"|Kaplan-Meyer|-|colspan="2"|*'''Log rank test<br>= Mantel-Cox <math>\chi^2</math> test'''::<math>H_0</math> is event (survival) rates in each interval are all the same in two groups::<math>Log\ rank\ statistics = \frac{}{}</math>
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