What kind of test should I use for before and after treatment

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Discussion Overview

The discussion revolves around the appropriate statistical test to use for analyzing before-and-after treatment data from a study involving 30 subjects. Participants are considering tests to evaluate mean differences in blood measurements taken before and after treatment, specifically discussing the paired t-test and the Wilcoxon signed-rank test.

Discussion Character

  • Technical explanation
  • Debate/contested
  • Mathematical reasoning

Main Points Raised

  • One participant inquires about the appropriate test for mean differences in blood measurements before and after treatment, suggesting the paired t-test or Wilcoxon signed-rank test.
  • Another participant suggests that the choice of test depends on the type of measurements (nominal, ordinal, or interval) and assumes the blood measurements are interval and normally distributed, thus recommending the paired t-test.
  • A participant expresses confusion about the mention of using a binomial distribution with normal approximation, questioning its relevance to the current problem.
  • Another participant clarifies that the binomial distribution applies to success-failure type measurements, which do not seem relevant to the blood measurement data presented.
  • Concerns are raised regarding the validity of the analysis without a control group, with suggestions that a controlled experiment would provide a more robust comparison of mean changes.
  • Some participants agree on the necessity of using the same statistical test for before and after data, noting that variances may differ between the two datasets.
  • There is a discussion about the implications of using a control group and the conditions under which the t-distribution or Wilcoxon signed-rank test should be applied based on the distribution of the data.

Areas of Agreement / Disagreement

Participants express differing views on the appropriateness of using a binomial distribution in this context, with some asserting it is not applicable. There is also a lack of consensus on the necessity of a control group and the implications for the choice of statistical test.

Contextual Notes

Participants note that the appropriateness of statistical tests may depend on the distribution of the data and the presence of a control group, which remains unresolved in the discussion.

colstat
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What test or distribution should I use for before and after treatment?

Say, I have 30 subjects I test their blood before and after a pill they take a pill, what kind of test should I use?
I want to test mean difference, so, paired t-test? or Wilcoxon signed rank test?
The data looks like this

person before after
#1 100 89
#2 90 75
#3 120 100
#4 132 130
... ... ...
#30 141 120

I was told use binomial with normal approximation, but don't know why. I am so confused, how should I tell? someone please help. Thanks so much.
 
Last edited:
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Hi colstat! :smile:

It depends on the type of measurements you take.
Are they nominal, ordinal, or interval?
That is, how do you "test the blood"?

Your test results appear to be of type "interval".
For a blood measurement I would assume the measurements to be normally distributed.

So you would use the paired t-test implying the assumption of a normal distribution.
 
thanks! :) So, why am I told to use normal approximation to the binomial. I understand the normal part, but not the binomial part, where that does binomial come from?

Here is another site that actually explains it, but I am still confused
http://www.stat.yale.edu/Courses/1997-98/101/binom.htm

Thanks again!
 
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In the example the measurement is whether you attract the disease or not.
What is counted is the proportion of a group that attracts the disease.
This is binomially distributed.
But the proportion of a group can be approximated with the normal distribution.

In your current problem there's nothing that looks like a success-failure type of measurement so binomial does not come into play.
 
I was wondering about this, since the researcher himself said "binomial distribution z statistics with continuity correction."
Also, he said "The P values were calculated by comparing the observed proportion based on 29 patients..."

I am just thinking...what in the world?! why?

The article name is "Single-Site Botulinum Toxin Type A Injection for Elimination of Migraine Trigger Points"
 
Saying something like that implies a success-failure type of measurement.
You would need to dig up some more information about the measurement involved to be able to say more about it...
 
colstat said:
What test or distribution should I use for before and after treatment?

Say, I have 30 subjects I test their blood before and after a pill they take a pill, what kind of test should I use?
I want to test mean difference, so, paired t-test? or Wilcoxon signed rank test?
The data looks like this

person before after
#1 100 89
#2 90 75
#3 120 100
#4 132 130
... ... ...
#30 141 120

I was told use binomial with normal approximation, but don't know why. I am so confused, how should I tell? someone please help. Thanks so much.

Are these mean blood pressures, that is (S - D)/3)+D=MBP where S is systolic and D is diastolic? If so the last two are quite high, but the first two are low for either mean or systolic pressures, particularly 75.

In any case, these are considered continuous variables and MBPs or whatever you have (probably diastolic BP), would be expected to have a normal distribution. The correct way to test effectiveness of an intervention is with a placebo treated control group. You would then compare the mean changes in blood pressure based on the normal assumption for N1 and N2.

If you must compare before and after intervention in the same patients (no control), you should nevertheless use the same test for the before and after data since the variances may differ in the two data sets (unless you are able to use a population variance). In this case you would compare the mean before (N1) and after (N2) measured BP values. This, however, is not good science.
 
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SW VandeCarr said:
If you must compare before and after intervention in the same patients (no control), you should nevertheless use the same test for the before and after data since the variances may differ in the two data sets (unless you are able to use a population variance). In this case you would compare the mean before (N1) and after (N2) measured BP values. This, however, is not good science.

Agreed.

BTW, in case you don't know what a controlled experiment is, let me explain. A control group is a group of participants who, in your case, don't take the drug. They just basically live their normal, daily lives.

The experimental group, however, is the group that you're testing the effectiveness of the drug on.

You would calculate the mean blood pressure of the control group and the mean blood pressure of the experimental group.

If the blood pressures of both groups appear to be normally distributed, or you have determined that the Central Limit Theorem applies, you would use the t-distribution. If not, and the distribution is symmetric, you would use the Wilcoxon signed-rank test.
 
moonman239 said:
Agreed.

BTW, in case you don't know what a controlled experiment is, let me explain. A control group is a group of participants who, in your case, don't take the drug. They just basically live their normal, daily lives.

A control group should be as much like the treatment group as possible, except for the treatment itself. This usually is achieved by randomization, sometimes aided by matching on key variables.

f the blood pressures of both groups appear to be normally distributed, or you have determined that the Central Limit Theorem applies, you would use the t-distribution. If not, and the distribution is symmetric, you would use the Wilcoxon signed-rank test.

There are 30 subjects in the treatment group. With a matched control group, this should be sufficient for the Z test. The OP did list values in ascending order, but I'm not sure why. I don't see why a non-parametric test is indicated without more information.
 

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