Rick,   If I could get more help. Attached is my code. I have applied the code as you laid out, but I am not able to replicate previous numbers that I have calculating the RFI. I have studies A-D with the numerator and denominator in my datalines. I know from previous research that the RFI for each study is 5, 5, 10 and 4. I am trying to reproduce the same code so that I can use SAS moving forward for these calculations. Again, the goal is to see the minimum number of nonevents that need to change to an event for each outcome measure in order for the nonsignificant p-value, as measured by Fisher's exact test, to become significant. Alpha level 0.05. Any help is greatly appreciated. Thank you  data rfi; input study $ num1 denom1 num2 denom2; N = denom1 + denom2; sumEvents = num1 + num2; do x = 0 to SumEvents; /* write a 2x2 table for PROC FREQ to analyze */ Group=1; Event=1; Count=x; output; Group=1; Event=0; Count=denom1-x; output; Group=2; Event=1; Count=SumEvents-x; output; Group=2; Event=0; Count=denom2-SumEvents+x; output; end; datalines; A 3 151 3 149 B 3 151 2 149 C 5 125 2 50 D 3 57 2 60 ; run; ods select none; proc freq data=rfi; by study x; tables Event*Group / norow nocol nopercent; exact fisher; weight Count; ods output FishersExact=FisherOut(where=(Name1='XP2_FISH')); run; ods select all; proc sgpanel data=FisherOut; panelby study; series x=x y=nValue1 / markers; refline 0.05 / axis=y label='0.05'; colaxis grid values=(0 1 2 3 4 5 6 7 8 9 10) label="Num Events for Group 1"; rowaxis grid label="Two-Sided p-value"; run; data SolnLeftTail; set FisherOut(rename=(nValue1=pValue)); by Study; retain foundMax; if first.study then do; maxLeftEvents = .; foundMax = 0; end; if NOT foundMax then do; if pValue <= 0.05 then do; maxLeftEvents = x; output; end; else foundMax = 1; end; run; proc print data=SolnLeftTail; var Study x pValue; run; *RFI- Study A - 5 Study B - 5 Study C - 10 Study D - 4;   ... View more

Rick, You understand the setup of my datalines correctly.   The idea is to find the minimum number of events that need to change in order to reverse the pvalue from >0.05 to <0.05. It looks like the code you provided shows that. Is it possible, instead of on a graph, to show a table of the changes? Something like below:   # of events changed            Pvalue(hypothetical) 1                                                0.061 2                                               0.053 3                                               0.047       ... View more

I am trying to find an efficient way given just this information that I can calculate how many non-events would need to become events to make the pvalue significant using a two-tailed Fisher's exact test. My datalines are below for the 2 studies I am looking at. Datalines will likely be how I have to create a data set to start, so, if possible, a starting point like my datalines would be helpful. Thank you data dataset; input study $ num1 denom1 num2 denom2 pvalue; datalines ; A 14 33 8 37 0.071 B 10 33 5 37 0.143 ; run; ... View more

Do you have any recommendations if I am not able to use proc iml? ... View more

Yes, this is a 2x2 table. Disease is a binary and I have a binary grouping variable.  ... View more

The test is a Chi Square or Fisher's exact.    Would you have an example of what a loop like that would look like? Thank you  ... View more

data update1(drop= var75 -- var77); retain varlist; update raw(in=a) ss(in=inb); by key date type; if a then output; run; This is the code I have run to update my data.  ... View more

Apologies not proc update, but a data step using the update statement.  ... View more

Thank you. That was an oversight on my part. ... View more

I checked my code and I previously set the length to 20 to make sure I had room for any longer strings that could be in the data set. Is there any options for this scenario? Also, fakessn. is not a format I have available. Thank you ... View more