What kind of statistical test can be used for my data?

#1
It is my first post on this forum so please be gentle. If it is not a proper section I would appreciate if moderator moves the thread to the correct one.

I am stack with this problem for some time already...

Let's say hypothetically I need to compare samples taken from group of humans at the day and at the night. I would like to see if there are any significant changes in the samples between those two time points. There are different samples (18 in total), for example blood, urine, spit, etc... I have four replicates for each time point. Each team/group is a composition of different people (male, female, young, old, etc) and the number in each group may be different as well. That means Sample 1 (blood) was taken from 5 people and I calculated a mean. So I used the easiest approach and I just took a mean of the results for each group/team but I am not sure if it should be done like that. Anyway, the results are shown below:

Day:
Code:
> dput(data1)
structure(list(Sample = 1:18, `Replicate 1` = c(483139957.466999, 
18419484.8793012, 6323582.65012894, 4835513.9449211, 18825930.9961964, 
3345329.29658372, 10991207.7733899, 11543788.4022557, 37433260.659815, 
52656998.4104276, 4630965.58466113, 7989791.52375088, 5869587.5844277, 
4851157.10912223, 8319804.52469405, 26480159.0093267, 14312197.2102269, 
2622934.76077158), `Replicate 2` = c(430115690.772298, 21746370.57802, 
5117948.43432065, 900198.599477471, 18036003.7406036, 2613255.31600864, 
12628842.5152089, 16829082.1454364, 20833464.069239, 41704022.4059303, 
3224551.81607163, 9531731.20650826, 4622904.13493909, 4594932.39864943, 
8237590.6183486, 24161835.5144514, 22254270.0518872, 2493331.3326573
), `Replicate 3` = c(367285858.792061, 17505038.9708625, 9115997.19573197, 
3017212.56266055, 18737371.5138656, 3235286.82979338, 11851406.2728674, 
8355830.47176874, 13394694.3199866, 47309374.9965771, 4945726.7939656, 
8778605.82132967, 5550794.63124474, 7339020.02097186, 8402907.89430717, 
37094084.0472019, 23193128.0376071, 1112871.90011314), `Replicate 4` = c(413568675.025335, 
20064022.1599402, 7773013.05600225, 4254021.07399388, 24150780.1134545, 
4101556.77813632, 8378739.17697561, 12711332.3613856, 32092851.1380528, 
21539261.3107248, 3432039.98399363, 7802961.67410367, 6561871.72983466, 
5875588.43914924, 11466196.1253827, 33427822.1313595, 33166052.5207409, 
4788465.84362014)), .Names = c("Sample", "Replicate 1", "Replicate 2", 
"Replicate 3", "Replicate 4"), row.names = 2:19, class = "data.frame")
Night:

Code:
> dput(data2)
structure(list(Sample = 1:18, `Replicate 1` = c(353623172.869356, 
11571655.7857434, 8104862.69916794, 3799746.12789339, 21085349.9524958, 
2387774.69393264, 12213154.0833913, 10918319.9666355, 29408897.8409511, 
56173957.7386867, 4025995.93106508, 7293493.20054593, 4814461.17385978, 
7142677.49114559, 8293092.20154457, 32394546.169772, 15099008.2859653, 
1821668.51961212), `Replicate 2` = c(424954138.16318, 22047234.918163, 
3991307.57211047, 686033.835602487, 19175437.5284624, 2579579.45862803, 
7805661.23361268, 14880672.2135273, 20106717.6877472, 56120888.9344651, 
3594835.93740008, 9005342.77715287, 5072612.73581937, 6282840.2470555, 
8095341.84525128, 40915897.2583209, 20942848.6480902, 1532641.25411947
), `Replicate 3` = c(341343891.665324, 23343840.5736713, 4784478.52343266, 
3794454.787824, 19608611.2296076, 1812322.82994808, 8500655.49282534, 
7449578.76682836, 30177450.6772738, 38022069.3055181, 3752212.94125585, 
8461228.01641203, 4294351.62196396, 3792939.77566062, 8561121.77342389, 
23677730.1782989, 32512066.4606989, 1547156.89308365), `Replicate 4` = c(524410338.96904, 
12087790.894342, 6440340.32357233, 2825622.25610684, 25733703.0907116, 
1967066.96054326, 5898461.97653573, 10954022.0570318, 26916007.3958975, 
18512737.6244699, 3214702.78720154, 7174077.63370964, 6155566.585692, 
5070975.61705348, 7824657.48924661, 36340170.8005276, 20648969.5206572, 
2102068.53223516)), .Names = c("Sample", "Replicate 1", "Replicate 2", 
"Replicate 3", "Replicate 4"), row.names = 2:19, class = "data.frame")
Of course the composition of directly compared teams is the same (for replicates and time points). That means for example in Sample 1 the group was formed by the same 5 people.

I did a t-test to compare those results but... I can't see any significance there but I am sure that there should be some. The question is if I should change the significance test or change the whole approach... Any ideas ?
 

rogojel

TS Contributor
#2
hi,
you could keep the original measurements (i.e. without forming groups) and just do a paired t-test.
This is more sensitive then the t-test, so if there is a small effect you would have better chances to see it.

regards