Evaluation ☑️ [Surveys]

posted by Helmut Homepage – Vienna, Austria, 2020-06-03 14:36 (906 d 20:47 ago) – Posting: # 21497
Views: 13,710

[image]Dear all,

here are the results of 101 respondents as of 23 October.
THX to all participants (the survey is closed). 1

Below the questions percentage of complete answers in decreasing order. Since in some questions multiple choices are possible, the percentage can be >100%. Not disclosed information excluded.

Below each question my very personal opinions on the outcome.
[list=1][*]How do you estimate the sample size?
○ Software

    64%
○ Both
    34%
○ Sample size tables
      2%

[*]Which software do you use?
☐ Open source (e.g., R-packages like PowerTOST, bear, …)

    53%
☐ Free (e.g., FARTSSIE, EFG, …)
    44%
☐ Commercial (off-the-shelf, e.g., SAS Proc Plan, NQuery Advisor, PASS, StudySize, …)
    31%
☐ In-house (e.g., own SAS-macros, R, C, Excel-template, …)
    14%
☐ Web-based
      3%
☐ Optional: Please give the software you use most (incl. version, year of release)
    PowerTOST (5), FARTSSIE (3), SAS (3), PASS (2), Julia: ClinicalTrialUtilities (1), NQuery (1), SPSS (1),
    Statistics101 Resampling Simulator (1), WinNonlin (1)

[*]How often do you update the software you use most?
○ Occasionally

    41%
○ Regularly
    36%
○ Never
    20%

[*]Is the software you use most validated?
☐ Cross-validated with other software

    30%
☐ Comparison with sample size tables
    29%
☐ IQ (Installation Qualification acc. to procedures provided by the vendor)
    23%
☐ No
    23%
☐ PQ (Performance Qualification)
    16%
☐ OQ Type 1 (Operational Qualification acc. to procedures provided by the vendor)
    14%
☐ Partly (i.e., only some of the procedures)
    10%
☐ OQ Type 2 (Operational Qualification acc. to own pre-specified procedures)
      6%
☐ Other approach (please specify)
      5%

[*]Were you ever asked by a regulatory agency about software validation?
☐ No

    82%
☐ Yes
    15%
☐ Optional: If you answered “Yes”, please give the year
    Four answers: 2019 (2), 2018, 2017

[*]Do you repeat the estimation in-house if provided by an external entity (CRO, sponsor, consultant)?
☐ Always

    55%
☐ Regularly
    21%
☐ Sometimes
    17%
☐ Never
      7%

[*]Do you perform a Sensitivity Analysis in order to assess the impact on power if in the study values (e.g., T/R-ratio, CV, number of dropouts) will deviate from assumptions?
○ Always

    37%
○ Sometimes
    34%
○ Never
    14%
○ I don’t know what a Sensitivity Analysis is
    11%

[*]Do you increase the estimated sample size according to the expected dropout rate?
○ Yes (chosen by management)

    37%
○ Yes (formula: n’ = n × (100 + dropout-rate in %) / 100)
    29%
○ Yes (formula: n’ = n / (100 – dropout-rate in %) × 100)
    22%
○ Yes (as provided by the software; I don’t know the formula)
      9%
○ No (since the impact on power is limited)
      3%

[*]Please give general problems that you faced in sample size estimation.
☐ Estimated sample size was substantially smaller/larger than expected
(compared to PARs / other studies)

    41%
☐ Result of re-assessment differed from the estimate given (by CRO, sponsor, consultant)
    37%
☐ Software, version, setup not given (by CRO, sponsor, consultant)
    28%
☐ Other (please give a short description)
    10%

[*]Did you face problems with the software you use most?
☐ No

    56%
☐ Planned design not available
    20%
☐ User manual insufficient
    (too short/verbose, methods not/poorly documented, lacking/outdated references, …)

    16%
☐ Only one design-variant provided (although alternatives exist)
      9%
☐ Methods based on simulations not reproducible (e.g., for reference-scaling)
      9%
☐ Operation is complicated
      8%
☐ Other (please specify)
      4%
[/list]

[list=1][*]Since the survey is not public (I’ve send out invitations by e-mail): Some participants answered only the first question and skipped all the others. That’s not helpful.
[*]Not like in “free beer” but like in “free speech”.[/list]

The IP is not recorded, only the country:
India (27), Russia (12), Germany (10), Spain (8), Czechia (7), Jordan (5), USA (5), Austria (2), China (2), Mexico (2), The Nether­lands (2), Po­land (2), Ukraine (2), Australia (1), Bela­rus (1), Brazil (1), Den­mark (1), Egypt (1), France (1), Greece (1), Italy (1), Por­tu­gal (1), Slo­venia (1), South Africa (1), Taiwan (1), Tanzania (1), Turkey (1), UK (1), Uruguay (1).

Dif-tor heh smusma 🖖🏼 Довге життя Україна! [image]
Helmut Schütz
[image]

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