Tanta Innovators Association

DTCP Tanta Recruitment Wave 1 Delta Thalassemia Center for Control and prevention (DTCP) is scientifically recognized as a non-profit organization (NPO) funded by Science and Technology Development Fund (STDF). The center is conducting its first Multi-center screening study" prevalence of Thalassemia carriers relative to Thalass...

هنكمل كلامنا عن sensitivity and specificity
وعشان نفهم اكتر هنطبق اللي قولناه امبارح علي مثال عملي

A new test for diagnosis of hepatitis C is applied to 500 individuals, the test indicated that 53 of them are diseased and 400 of them are not.
Actually 70 patients are suffering from the disease while 430 are not.
(We know that: * Sensitivity = True +ve / (True +ve + False -ve)

* Specificity = True -ve / (True -ve + False +ve)
So, we have to identify the previous terms, and we will get the following: True +ve: 53
True -ve: 400
False +ve: 30
False -ve: 17
Total: 500
Sensitivity = 53 / (53+17) = 0.7
Specificity = 400 / (400+30) = 0.9
Finally,sensitivity and specificity which are used for evaluating the clinical tests and give us a statistical measurements of their values and compare them with the current Gold Standard test (a test gives the best diagnosis of a given disease

عيدنا واجزنا نرجع تاني للاحصاء بتاعتنا =D

In this week, we are going to talk briefly about sensitivity and specificity

Is the patient has the disease? Yes / No
What is the result of the test? Positive / Negative

and we will get one of the following:
1- The patient has the disease and the test result is positive, this is called a “True +ve”
2- The patient has the disease and the test failed to indicate that: False -ve.”

3- The patient doesn't have the disease and the test result is positive: “False +ve”
4- The patient doesn't have the disease and the test result is negative: “True -ve”

* Sensitivity = True +ve / (True +ve + False -ve)
This means that the sensitivity of a given test is the ability of that test to indicate 'correctly' the DISEASES individuals and the result rages from 0 to 1.
The perfect sensitivity is 1, in this case the test can indicate all patient with the disease correctly. In other words: High sensitivity | Negative test | role out.

* Specificity = True -ve / (True -ve + False +ve)
This means that the specificity of a given test is the ability of that test to indicate correctly the HEALTHY individuals and the result also results from 0 to 1.
A test with perfect sensitivity (which is 1) can indicate all healthy individuals correctly. In other words: High specificity | Positive test | role in.

بوست النهاردة مميز جدا اولا عشان ده بوست ليلة العيد
ثانيا عشان اخر بوست عن الاحصاء الاستدلالية
وعشان العيد فرحة مش هنتقل عليكم كفاية الكحك =D
فيه هنعرف ازاي نحسب C.I
وايه العوامل اللي هتاثر عليه
Calculating the interval width
These factors that influence the width of a 95 per cent confidence interval
1 Variability in the data
We know that a high SD tends to spoil samples. So, if the SD is large, our sample will be relatively unreliable and the true population mean might be considerably higher or lower than our sample suggests. We will therefore have to set the interval relatively wide to ensure that we include the real population mean.
2 Sample size
With larger samples we will get estimates that are closer and closer to the truth, so we can afford to make the interval narrower.

To summarizes the situation. An increase in SD will lead to a wider interval and increasing the sample size will reduce its width.
Width of confidence intervals
Greater SDs give wider intervals.
Greater sample sizes give narrower intervals.

مكملين مع الاحصاء الاستدلالية
confidence intervalهنتكلم عن

What is a confidence interval?

We have already established that a mean derived from a sample is unlikely to be a perfect estimate of the population mean. Since it is not possible to produce a single reliable value, a commonly used way forward is to quote a range within which we are reasonably confident the true population mean lies. Such a range is referred to as a ‘confidence interval’.

The mean derived from the sample remains the best available estimate of the population mean and is referred to as the ‘point estimate’. We add and subtract a suitable amount to the point estimate to define upper and lower limits of an interval.
We then state that the true population mean probably lies somewhere within the range we have now defined.

وطبقا لمقوله اشركني وسوف افهم فاحنا مش هنفهم الكلام ده غير بالمثال
يعنى انا واثق بنسبة اد ايه
ان ال True population parameter قيمته تقع فى هذا ال interval
Statisticians can calculate a range (interval) in which we can be fairly sure (confident) that the true value” True population parameter lies"
مثال :
In a study of a new treatment of insomnia the research concluded that the new treatment increased the sleeping hours by a mean 2 hours with 95% CI (1.5:2.5) hours
يعنى هذا العلاج الجديد زود ساعات النوم فى العينة اللى تم عليها الدراسة بمتوسط زيادة ساعتين
طيب بالنسبة لل population هنا الاحصاء بتساعدنا
To estimate the Confidence Interval
95%CI (1.5:2.5) hours تعنى ان انا واثق بنسبة 95% ان القيمة الحقيقية اللى هنلاقيها فى ال population تقع بين 1.5 الى 2.5 ساعة زيادة فى عدد ساعات النوم

عشان نعرف العوامل اللي بتاثر علي حساب ال CI
ده هيكون في بوست العيد
وهيكون باذن الله اخر بوست في الاحصاء الاستدلالية
#يتبع

Inferential Statistics
للاحصاء الاستدلالية بقية .....
هنتكلم النهارده عن حاجة مهمة جدا وهي P value

When is it used?
The P (probability) value is used when we wish to see how likely it is that a hypothesis is true. The hypothesis is usually that there is no difference between two treatments, known as the “null hypothesis”.
What does it mean?
The P value gives the probability of any observed difference having happened by chance.
Def: P value is the probability that what we have concluded is wrong

P = 0.5 means that the probability of the difference having happened by chance is 0.5 in 1, or 50:50.
P = 0.05 means that the probability of the difference having happened by chance is 0.05 in 1, i.e. 1 in 20.

P value frequently quoted as being “statistically significant”, i.e. unlikely to have happened by chance and therefore important.

The lower the P value, the less likely it is that the difference happened by chance and so the higher the significance of the finding.

The “null hypothesis” is a concept that underlies this and other statistical tests.
The test method assumes (hypothesizes) that there is no (null) difference between the groups. The result of the test either supports or rejects that hypothesis.
The null hypothesis is generally the opposite of what we are actually interested in finding out. If we are interested if there is a difference between two treatments then the null hypothesis would be that there is no difference and we would try to disprove this.

Try not to confuse statistical significance with clinical relevance. If a study is too small, the results are unlikely to be statistically significant even if the intervention actually works. Conversely a large study may find a statistically significant difference that is too small to have any clinical relevance.


P value (significance) قيمتها:
هى قيمة عشرية تتراوح بين 0 & 1
واتفق علماء الاحصاء الطبية على ان :
If P value < 0.05, then the results are statistically significant.
If P value > 0.05, then the results are not statistically significant.
How to calculate P value:
By using statistical tests which varies according to the variables in the study
البوست طويل شوية
#يتبع

رمضان السنة دي مختلف خالص لانه قبل ما يخلص كده
هنتكلم عن موضوع مهم وهو Inferential Statistics :o :o

Inferential Statistics

With inferential statistics, you are trying to reach conclusions that extend beyond the immediate data alone. For instance, we use inferential statistics to try to infer from the sample data what the population might think. Thus, we use inferential statistics to make inferences from our data to more general conditions; we use descriptive statistics simply to describe what's going on in our data.

عشان نفهم اكتر التجربة خير دليل
لو عاوزين نعرف اوزان الاطفال اللي سنهم 6 سنين ؟؟ هنعمل ايه
اكيد مش هنجيب كل الاطفال ونشوف وزنهم
هناخد هينة عشوائية من الاطفال اللي عندهم 6 سنين ونقيس اوزانهم
عشان اطبق نتيجة العينة علي كل الاطفال هنا هيجي دور الاحصاء الاستدلالية

بوست_العيد

كل عام و أنتم بخير بمناسبة حلول شهر رمضان الكريم. أعاده الله علينا و عليكم باليمن و البركات.

TIA wishes everyone a spiritually blessed Ramadan.

Our congratulations Dr. Mohamed Abd Elrahman "President of Tanta Innovator Association" & his wife Dr. Asmaa Abd Elgelil for the arrival of your new baby girl ^_^
This is such great news!! We’re really thankful and excited that your new baby girl has arrived safe and sound. May you both find parenthood a wonderful and rewarding experience.
All the very best and with lots of love. :)

★ Systematic Review:
- A summary of the clinical literature. It is a critical assessment and evaluation of all research studies that address a particular clinical issue.
- The researchers use an organized method of locating, assembling, and evaluating a body of literature on a particular topic using a set of specific criteria.
- A systematic review typically includes a description of the findings of the collection of research studies.
- The systematic review may also include a quantitative pooling of data, called a meta-analysis.

★ Meta-Analysis:
- A statistical process that combines the findings from individual studies.

★ FINER criteria of a good research question:

• Feasible: Is the question answerable?
•Interesting: The question has to be interesting to the investigator, but should also be interesting to others.
• Novel: Has this study been done before? Does it add to the current body of medical knowledge?
• Ethical: Can the study be done in a way that does not subject subjects to excess risks?
• Relevant: Will it further medical science?