Normalizing Hormone Secretion: Grubb's Test Results

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In summary, when normalizing secretion of a hormone to total cellular content, outliers may appear in the resulting values even if there were no outliers in the original data. However, outlier tests should not be the sole basis for excluding data, and instead should be used as a starting point to examine specific cases and determine if there was a potential experimental error. In some cases, it may be appropriate to exclude a data point without fully understanding the experimental error, as long as it is disclosed and explained.
  • #1
bacondoodle
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Hi,

I have measured secretion of a hormone and I am normalizing it to the total cellular content of the hormone. I have used Grubb's test for determining outliers (GraphPads online calculator) and there are no outliers in the values for amount of secreted hormone, nor for hormone content. However, when I normalise it (secreted hormone / total hormone content) there are outliers in the resulting values. Should I exclude them even if there are no outliers in the original data?

Thanks
 
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Generally you do not exclude outliers unless there is a specific experimental reason to do so. Like a machine malfunction or user error.

Outlier tests should not be used as a basis to exclude data. Instead they should be used as a basis to examine specific cases and see if there was some kind of experimental error.
 
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  • #3
bacondoodle said:
However, when I normalise it (secreted hormone / total hormone content) there are outliers in the resulting values.

As I understand the situation, both secreted hormone ##S(i)## and total hormone content ##T(i)## vary from sample to sample. Grubbs test assumes you are testing a normally distributed population. If ##S## and ##T## are normally distributed, the ratio ##S/T## isn't normally distributed. So, theoretically, Grubbs test does not apply to ##S/T##.

In practical situations it isn't impossible that a random variable that is not normally distributed by theory can still be approximated by a normal distribution. However, you should determine that the normalized values ##S/T## do have an approximate normal distribution before paying attention to the results of a Grubbs test for outliers on the normalized values.
 
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Dale said:
Generally you do not exclude outliers unless there is a specific experimental reason to do so. Like a machine malfunction or user error.

Outlier tests should not be used as a basis to exclude data. Instead they should be used as a basis to examine specific cases and see if there was some kind of experimental error.
I agree, with one caveat. Suppose there is some reason to know that a data point can not be correct or is just way too rare to be expected in a sample of that size. In my opinion, it can be excluded even without understanding what may have gone wrong experimentally. The reason requires knowledge of the subject that is independent of the experimental result.
 
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FactChecker said:
Suppose there is some reason to know that a data point can not be correct or is just way too rare to be expected in a sample of that size.
In the end, the important thing is to disclose the exclusion of the data and explain the reasons. Then, the scientific community can agree or disagree through peer review and citations.
 
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1. What is Normalizing Hormone Secretion?

Normalizing hormone secretion refers to the process of maintaining a balanced level of hormones in the body. Hormones play a crucial role in regulating various bodily functions, and an imbalance in their secretion can lead to health issues. Normalizing hormone secretion is important for overall health and well-being.

2. What is Grubb's Test and how is it related to Normalizing Hormone Secretion?

Grubb's Test is a diagnostic test used to assess the function of the pituitary gland, which is responsible for regulating hormone secretion. This test measures the levels of certain hormones in the blood, such as growth hormone, cortisol, and prolactin. The results of this test can help identify any abnormalities in hormone secretion and guide treatment for normalizing hormone levels.

3. What are the common reasons for abnormal hormone secretion?

There can be various reasons for abnormal hormone secretion, including genetic disorders, tumors, stress, certain medications, and medical conditions affecting the pituitary gland or other hormone-producing organs. It is essential to consult a healthcare professional for proper diagnosis and treatment of any hormonal imbalances.

4. What are the symptoms of abnormal hormone secretion?

The symptoms of abnormal hormone secretion can vary depending on which hormones are affected. Some common symptoms may include weight gain or loss, changes in appetite, fatigue, mood swings, irregular periods, excessive hair growth, and changes in libido. It is important to note that these symptoms can also be caused by other health issues, so consulting a doctor is crucial for proper diagnosis.

5. How is Normalizing Hormone Secretion achieved?

The treatment for normalizing hormone secretion depends on the underlying cause of the imbalance. In some cases, medication may be prescribed to regulate hormone levels, while in others, surgery or other interventions may be necessary. Lifestyle changes, such as maintaining a healthy diet and managing stress, can also help in normalizing hormone secretion. It is important to work closely with a healthcare professional to determine the best course of treatment for each individual case.

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