## Power in Diletti's sample size table [R for BE/BA]

Dear all,

I performed some comparisons of the code based on Jones/Kenward implemented in

All comparisons were done for CV=20% with ratios of 0.85-1.20. Dilleti reported sample sizes to obtain >80% power, calculated odd sample sizes were reported rounded up to the next even number (

Power with sample sizes given by Diletti

A Monte Carlo Simulation (1000000 runs) for GMR=1.05 and 18 subjects in StudySize resulted in:

Power

Differences may be due to the implementation of the algorithm to obtain the value of the noncentral

Maybe somebody of you has access to SAS or software specialized in power analysis (

I performed some comparisons of the code based on Jones/Kenward implemented in

**R**, Diletti's table and results obtained from StudySize (v2.0.1). Quite interesting...All comparisons were done for CV=20% with ratios of 0.85-1.20. Dilleti reported sample sizes to obtain >80% power, calculated odd sample sizes were reported rounded up to the next even number (

`underlined`

):```
+======+=====+===========+===========+
```

| GMR | n | R-code | StudySize |

+------+-----+-----------+-----------+

| 0.85 | 134 | 0.8014178 | 0.80167 |

| 0.90 | 38 | 0.8140704 | 0.81536 |

| 0.95 | 20 | 0.8300156 | 0.83451 |

| 1.00 | 16 | 0.8214263 | 0.83305 |

| 1.05 | 18 | 0.7950343 | 0.79996 |

| 1.10 | 32 | 0.8084890 | 0.80992 |

| 1.15 | 72 | 0.8035456 | 0.80411 |

| 1.20 | 294 | 0.8017617 | 0.80182 |

+======+=====+===========+===========+

Power with sample sizes given by Diletti

*et al.*at a GMR of 1.05 were below 80%, calculated both with**R**and StudySize...A Monte Carlo Simulation (1000000 runs) for GMR=1.05 and 18 subjects in StudySize resulted in:

Power

`0.8006`

(95% coverage probability: `0.7998-0.8013`

).Differences may be due to the implementation of the algorithm to obtain the value of the noncentral

*t*-distribution by numeric integration...Maybe somebody of you has access to SAS or software specialized in power analysis (

*e.g.*, PASS or nQuery Advisor) and would like to check these results?—

Helmut Schütz

The quality of responses received is directly proportional to the quality of the question asked. 🚮

Science Quotes

*Dif-tor heh smusma*🖖Helmut Schütz

The quality of responses received is directly proportional to the quality of the question asked. 🚮

Science Quotes

### Complete thread:

- R-Code for Power in 2×2 Cross-over Helmut 2006-12-28 21:33 [R for BE/BA]
- Power in Diletti's sample size tableHelmut 2007-01-01 23:59
- Approximate Power Helmut 2007-01-06 15:17
- Power Calculation for replicate crossover design mathews 2008-04-03 13:19
- Power Calculation for replicate crossover design Helmut 2008-04-03 13:49
- Power Calculation for replicate crossover design mathews 2008-04-04 13:21

- Power Calculation for replicate crossover design Helmut 2008-04-03 13:49
- Exact Power Helmut 2009-09-25 19:20
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- Al Gore Rhythms Helmut 2009-09-29 14:52

- 42! SASophylistic power oracle d_labes 2009-09-29 13:37
- All the important answers are here! yjlee168 2009-09-29 23:49

- All the important answers are here! Helmut 2009-09-28 23:18

- All the important answers are here! Helmut 2009-09-28 19:52

- All the important answers are here! ElMaestro 2009-09-28 19:12

- Software validation Helmut 2009-09-28 15:21

- Exact Power ElMaestro 2009-09-27 23:27

- Power Calculation for replicate crossover design mathews 2008-04-03 13:19

- Approximate Power Helmut 2007-01-06 15:17
- R-Code for Power in 2×2 Cross-over KDA 2019-01-23 04:24
- R-Code for Power in 2×2 Cross-over Ohlbe 2019-01-27 18:24

- Power in Diletti's sample size tableHelmut 2007-01-01 23:59