|
Size: 1061
Comment:
|
Size: 1060
Comment:
|
| Deletions are marked like this. | Additions are marked like this. |
| Line 1: | Line 1: |
| Line 4: | Line 3: |
| Newcombe(1998) further goes on to compare various methods for giving confidence intervals for the difference in a pair of proportions from two different groups. he concludes that the Wald confidence interval is biased when the difference in proportions is close to zero or (+/-) one. As for a single proportion he recommends the two-sample analogue of the Wilson one-sample confidence interval. | Newcombe (1998) further goes on to compare various methods for giving confidence intervals for the difference in a pair of proportions from two different groups. he concludes that the Wald confidence interval is biased when the difference in proportions is close to zero or (+/-) one. As for a single proportion he recommends the two-sample analogue of the Wilson one-sample confidence interval. |
| Line 6: | Line 5: |
| This excel [attachment:bin2.xls spreadsheet] computes the two sample analogues of the methods in the one-sample spreadsheet. | This EXCEL [attachment:bin2.xls spreadsheet] computes the two sample analogues of the methods in the one-sample spreadsheet. |
Improved confidence limits for comparing two independent binomial proportions
Newcombe (1998) further goes on to compare various methods for giving confidence intervals for the difference in a pair of proportions from two different groups. he concludes that the Wald confidence interval is biased when the difference in proportions is close to zero or (+/-) one. As for a single proportion he recommends the two-sample analogue of the Wilson one-sample confidence interval.
This EXCEL [attachment:bin2.xls spreadsheet] computes the two sample analogues of the methods in the one-sample spreadsheet.
References
Moore DS & McCabe GP (2006) Introduction to the practice of statistics (5th ed.). WH Freeman:New York. (This mentions the two sample analogue of the Agresti-Coull method which was not mentioned in the original paper which dealt with the one-sample case).
Newcombe RG (1998) Interval estimation for the difference between independent proportions: comparison of eleven methods. Statistics in Medicine 17 873-890.