Reporting data analysis methods in high impact respiratory journals

Abstract

Data analysis methods play an important role in respiratory research. We evaluated the application and complexity of data analytical methods in high-impact respiratory journals and compared the statistical reporting in these respiratory articles with reports published in other eminent medical journals. This study involved a total of 160 papers published in 2015 in the European Respiratory Journal,

Statistical Methods in Human Resource Research: Dearth or Diversity? Evidence from Published Literature

“…Arnald et al (2013) did a research in medical field and reported that there was increased use of advanced statistics such as multivariable regression, multilevel modelling, survival and sensitivity analysis. In another research within the same field, Nieminen et al (2018) found that traditional statistics for comparing independent groups such as chi-square test, t-test and ANOVA were commonly used. Within library and information science Zang et al (2016) found a growth trend in five out of six journals in the usage of statistics.…”

“…The researchers went on to propose the use of bathtub modelling and optimal matching analysis. Medical field has robust and diversity of studies (Arnald et al, 2013;Nieminen et al, 2018) investigating the statistical models used in this field. Information and library science has a good number of studies (Zhang et al, 2016(Zhang et al, , 2018 exploring the use of statistics in the field.…”