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Hi Satya. If prevalence is 1.4% ….. please look for some other articles also …. If you get a range of prevalence from 1 to 1.8% (for example)….then please take precision as 0.4…. Please try that way

@@PublicHealthResearchDrSandheep okay thank you so much sir for your kind response, i ll try that way and get back to you..

Sample size = [(z alpha) x (z alpha) x p x (1 - p) ] / (precision x precision)

@@PublicHealthResearchDrSandheep So where did you calculated the Prevalence (P) of those 600 students from the college Thank you for your time and helping me

Prevalence can be taken from the previous research article - on the similar research topic - conducted in a similar population. If similar research article is not available. We can anticipate the prevalence as 50% - as it gives the highest sample size

anticipated difference in mean values and sd of difference in means (in case of pre and post test comparisons)

thank you for watching and commenting 😊

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987 is the sample size Proportion is 28% …. relative precision of 10% means absolute precision is 2.8% ….. alpha error of 5% means confidence level is 95%

will do. Thank you so much

sample size calculation for rct is different. Outcome variable can be any one of the following - difference in proportions between experimental group and control group OR difference in mean values of continuous variable between experimental group and control group

If you need more detailed explanations, I will make a video

@@PublicHealthResearchDrSandheep thank you sir 🙏

Please enquire about the average number of patients from the tertiary hospital. If you don’t know exact numbers, you can take approximate numbers

sorry for the delay in replying

you can define the sampling frame ( can include all the admitted patients with internal malignancy - from selected hospital or hospitals). Then define the duration of the time period. All those admitted with internal malignancy during that period in those selected hospitals - constitute N (it is a hypothetical scenario)

Thank you so much 🙏

Thank you so much 🙏

thank you so much for your kind support and feedback. You can suggest me the topic. I will try to create videos on those topics 🙏

Thank you so much for your feedback and support

Thank you so much 😊🙏

Thank you so much for your kind feedback and support

Cochran,WG (1977). Sampling Techniques (3rd edition.). Wiley.

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Thank you so much for your kind comments

You are most welcome 🙏

in my understanding, you may use chi square test to compare the proportion of cows who got infested by ticks in different seasons of the year

you can assume that the prevalence is 50% - that assumption gives you the maximum possible sample size

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you are most welcome

Most welcome

thank you for your feedback

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Thanks a lot for your feedback 😊

If data is normally distributed - paired samples t test ….. if data is not normally distributed - Wilcoxon signed rank test

If you get the standard deviation of knowledge scores value and sample size from a previous similar published research -- you can calculate precision value 👍

yes sure

@@PublicHealthResearchDrSandheep Thank you so much

Please give anticipated prevalence as 50% and precision as 5%

Can you please clarify

Precision is = Z alpha * standard error of mean

standard error of mean = standard deviation / square root of n

Sorry I didn't mention those steps. But it's still the same, isn't it?

Yes it will be same 😊

drsandheep@gmail.com

you can take the middle value of the range as the anticipated frequency (my opinion…didn’t get any reference 🙏)

@@PublicHealthResearchDrSandheep thank u sir

you are most welcome

student can take the prevalence from other states in the same country / from nearby countries (with similar levels of health outcomes).

Please use 0.457 as P and 0.543 as 1 -P. Precision will be 0.05. Calculate the sample size substituting these values in the formula

If you don’t have information about P from previous research - please take P as 50% - or 0.5

Please use “stats” package. The command for estimation of single proportion is as follows sample_size <- power.prop.test( power = 0.8, p1 = proportion, precision = precision, sig.level = 0.05)

the scenario that is described in this video - is a study to estimate the value of mean (sd) of the outcome variable. Purpose of a case control study involving 2 means (for cases and controls) - will be to test the hypothesis. Hypothesis will be that there is no difference between the mean values among cases and controls

For case control study involving 2 means and sd, you can calculate the sample size using the formula for comparing the difference between means

​@@PublicHealthResearchDrSandheep Respected sir can u upload an example video on comparing the diferrence between means