Processing of Data Generated by 2-Dimensional Gel Electrophoresis for Statistical Analysis:  Missing Data, Normalization, and Statistics

2004 ◽  
Vol 3 (6) ◽  
pp. 1210-1218 ◽  
Author(s):  
Jinsook Chang ◽  
Holly Van Remmen ◽  
Walter F. Ward ◽  
Fred E. Regnier ◽  
Arlan Richardson ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Missing Data ◽  
Gel Electrophoresis ◽  
Data Normalization

Statistical Analysis with Missing Data.

Biometrics ◽  
1988 ◽  
Vol 44 (3) ◽  
pp. 913
Author(s):  
J. A. Derr ◽  
R. J. A. Little ◽  
D. B. Rubin
Keyword(s):  
Statistical Analysis ◽  
Missing Data

Statistical Analysis with Missing Data

2002 ◽  
Author(s):  
Roderick J. A. Little ◽  
Donald B. Rubin
Keyword(s):  
Statistical Analysis ◽  
Missing Data

scholarly journals Systematic review of statistical methods for safety data in malaria chemoprevention in pregnancy trials

2019 ◽  
Author(s):  
Noel Patson ◽  
Mavuto Mukaka ◽  
Kennedy N Otwombe ◽  
Lawrence Kazembe ◽  
Don P Mathanga ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Missing Data ◽  
Drug Safety ◽  
Safety Data ◽  
Malaria Prevention ◽  
Antimalarial Drugs ◽  
Controlled Trials ◽  
Safety Outcomes ◽  
In Pregnancy

Abstract Background Drug safety assessments in clinical trials present unique analytical challenges. Some of these include adjusting for individual follow-up time, repeated measurements of multiple outcomes and missing data among others. Furthermore, pre-specifying appropriate analysis becomes difficult as some safety endpoints are unexpected. Although existing guidelines such as CONSORT encourage thorough reporting of adverse events (AEs) in clinical trials, they provide limited details for safety data analysis. The limited guidelines may influence suboptimal analysis by failing to account for some analysis challenges above. A typical example where such challenges exist are trials of antimalarial drugs for malaria prevention during pregnancy. Lack of proper standardized evaluation of the safety of antimalarial drugs has limited the ability to draw conclusions about safety. We have therefore conducted a systematic review to establish the current practice in statistical analysis for antimalarial drug safety in pregnancy.Methods We searched PubMed, Embase, Scopus, Malaria in Pregnancy Library and Cochrane Central Register of Controlled Trials for original English articles reporting Phase III (randomized controlled trials) RCTs on antimalarial drugs for malaria prevention in pregnancy published from January 2010 to July 2019.Results Eighteen trials were included in this review that collected multiple longitudinal safety outcomes including AEs. Statistical analysis and reporting of the safety outcomes in all the trials used descriptive statistics; proportions/counts (n=18, 100%) and mean/median (n=2, 11.1%). Results presentation included tabular (n=16, 88.9%) and text description (n=2, 11.1%). Univariate inferential methods were reported in most trials (n=16, 88.9%); including Chi-square/Fisher`s exact test (n=12, 66.7%), t-test (n=2, 11.1%) and Mann-Whitney/Wilcoxon test (n=1, 5.6%). Multivariable methods, including Poisson and negative binomial were reported in few trials (n=4, 22.2%). Assessment of a potential link between missing efficacy data and safety outcomes was not reported in any of the trials that reported efficacy missing data (n=7, 38.9%).Conclusion The review demonstrated that statistical analysis of safety data in antimalarial drugs for malarial chemoprevention in pregnancy RCTs are inadequate. The analysis insufficiently account for multiple safety outcomes potential dependence, follow-up time and informative missing data which can compromise antimalarial drug safety evidence development, based on the available data.

scholarly journals Macrorestriction Fragment Profiles Reveal Genetic Variation of Cowdria ruminantium Isolates

2000 ◽  
Vol 38 (5) ◽  
pp. 1967-1970 ◽  
Author(s):  
E. P. de Villiers ◽  
K. A. Brayton ◽  
E. Zweygarth ◽  
B. A. Allsopp
Keyword(s):  
Genetic Variation ◽  
Statistical Analysis ◽  
Gel Electrophoresis ◽  
Profile Analysis ◽  
Pulsed Field Gel Electrophoresis ◽  
Dna Probes ◽  
Restriction Endonucleases ◽  
Pulsed Field ◽  
Cowdria Ruminantium

Macrorestriction profile analysis by pulsed-field gel electrophoresis (PFGE) was used to distinguish between seven isolates of Cowdria ruminantium from geographically different areas. Characteristic profiles were generated for each isolate by using the restriction endonucleases KspI, SalI, andSmaI with chromosomal sizes ranging between 1,546 and 1,692 kb. Statistical analysis of the macrorestriction profiles indicated that all the isolates were distinct from each other; these data contribute to a better understanding of the epidemiology of this pathogen and may be exploited for the identification of genotype-specific DNA probes.

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