calculation of t value and p-value of unpaired t-test

calculation of t value and p-value of unpaired t-test  




this program prompts for means, standard dev, and sample sizes of both groups, and calculates the p-value of unpaired t-test of two independent group.

<?
//-------------pdf_helper.inc --------------//
/*
This code is to compute a p-value from means of two groups.(not the paired data)  The paired t-test should be done with different df calculation

p-value is area under the curve from t* to infinity.
I used pdf of t distribution:
y=gamma[(v+1)/2)]/*[(1+(t^2/df)]^((-v-1)/2) 
    where gamma(alpha)=integral of [x^(alpha-1)*exp(-x)] from 0 to infinity  
There can be more than one form for distribution functions.  They are actually the same distribution function but in different ways to express it.
*/
 

//this function calculates t value(aka t statistics)
function getT($n1, $n2, $sd1, $sd2, $mn1, $mn2, $df)
{
     
    $var1=pow($sd1, 2);
     $var2=pow($sd2, 2);
    $pvar=(($n1-1)*$var1+($n2-1)*$var2)/$df;    

    if ($pvar>0) $t=($mn1-$mn2)/sqrt($pvar*(1/$n1+1/$n2));
    else $t=-9999;                            //no value
    if ($t>9999.999) $t=9999.999;                    //no value

    if(($var1/$n1+$var2/$n2)>0) $t=($mn1-$mn2)/sqrt($var1/$n1+$var2/$n2);
    else $t=-9999;                            //no value

    $t=abs($t);                            //since it's one sided test,
    echo "t value $t<br>";                        //we take the absolute value
    return $t;

}

//this function calculates area under the curve of gamma dist from 0 to 1
//function getGamma($alpha)

{
    $height=0;
    $sum=0;
    $width=0.1;
    for($i=0; $i<101; $i++)  $seg[$i]= $i/10;  
    for($k=0; $k<100; $k++)
        {
            $mp=($seg[$k]+$seg[$k+1])/2;  
            $height=pow($mp, $alpha-1)*exp(-$mp);
            $sum=($height*$width)+$sum;  
        }
    return $sum;
     
}
    
//this integrates t function from t* to infinity
function T_dist($df, $alpha1, $alpha2, $t)
{

/* t distribution integration */ 
$sum=0;
$t_seg[0]=$t;
$t_height=0;
$t_wd=(6-$t)/100;            //I just took 6 instead of infinity since the difference is 
$temp=pi()*$df;                //insignificant 

for($j=1;$j<101; $j++)  $t_seg[$j]=$t_seg[$j-1]+$t_wd;  
 for ($l=0; $l<100; $l++)
    {    

        $t_mp=($t_seg[$l]+$t_seg[$l+1])/2;  
        $t_height=($alpha1/(sqrt($temp)*$alpha2))*pow(1/(1+(($t_mp*$t_mp)/$df)), 1/2*($df+1));
        $sum=$t_height*$t_wd+$sum;
         
    }    
 
return $sum*2;

}    

?>    


//----------------mytest.php---------------//

<html>
<body>
 
<?
include("pdf_helper.inc");

//pdf_helper has formulas for several pdf(probability distribution functions) to derive p-values.
//p value is area under t*(t statistics) to infinity
 



/******************************************************/
Values needed to be loaded from MySQL(the surveyor)
*******************************************************/

$n1=3; $n2=3;         //n1= number of samples in group1; n2=number of samples in group2
$mn1=0.0629;        //mn1= mean from group1
$mn2=0.0775;        // mn2= mean from group2
$sd1=.0258;        // sd1= standard deviation of group1
$sd2=.0199;        //sd2=standard deviation of group2
 

$w1=($sd1*$sd1)/$n1;    //w1 and w2 are temp variables to calcuate df(degrees of freedom)
$w2=($sd2*$sd2)/$n2;
$df=pow(($w1+$w2), 2)/($w1*$w1/($n1-1)+$w2*$w2/($n2-1));  //calculation of df
$alpha1=($df+1)/2;
$alpha2=$df/2;


$t=getT($n1, $n2, $sd1, $sd2, $mn1, $mn2, $df);  //calculates t statistics
$pval=T_dist($df,getGamma($alpha1), getGamma($alpha2), $t);  //calculates p-value

echo "t statistics is $t<br>";
echo "p-value is $pval"; 


?>
</body>
</html>  From:
http://www.zend.com//code/codex.php?ozid=971&single=1
posted @ 2008-10-26 13:34  emanlee  阅读(1083)  评论(0编辑  收藏  举报