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Any help is much appreciated!! Im just querying some p values generated in SPSS from some data i have recently collected. The three groups were type 1 diabetes, type 2 diabetes and both together (type 1 and 2). Independent t tests were used to analyse depression (normal/ abnormal), fatigue (none/ severe) in relation to sedentary behavior. E.g is higher depression associated with increased sitting time. After collecting data for each group, i have come up with this data:

DEPRESSION: Type 1= 0.039 , Type 2= 0.05 , Type 1 and 2= <0.01

FATIGUE Type 1= 0.122 , Type 2= 0.012 , Type 1 and 2= <0.01

My question is how can the both group (type 1 and 2) be highly statistically significant if the other groups aren't? Does this look correct? Thank you!!

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    $\begingroup$ The p-values for depression and fatigue for type 1 and type 2 diabetes were significant or nearly significant. When you combine the two types you get a larger sample size and hence the p-value could easily go further down. $\endgroup$ Commented Apr 7, 2018 at 23:14
  • $\begingroup$ "Independent t tests were used to analyse depression (normal/ abnormal), fatigue (none/ severe) in relation to sedentary behavior." IT is vague. What are your hypotheses ? and objectives ? please be specific . $\endgroup$
    – user10619
    Commented Apr 11, 2018 at 16:47

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an example with the same (more clear) effect:

        a=0   a=1    mean
b=0     11    39     25 
b=1     41    9      25
mean    26    24     25

Note that the mean values are very similar, $\mu_{a=0} \sim \mu_{a=1}$ and $\mu_{b=0} \sim \mu_{b=1}$, all around 25.

But the corner-cells are very different from the mean cell value 25. So if you compare 'a=1 and b=1' with 'a != 1 or b !=1' the you will find a big difference.

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