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Covariate adjustments used in multivariate analyses were selected from a backward selection with a p-value less than 20%.
The subjects in genome-wide (stage 1) and replication (stage 2) analyses were selected from KORA S3 and S4 surveys, respectively.
The genes used in phylogenomic analyses were selected from sets of orthologs, identified as reciprocal best BLAST hits and validated through comparison with the COG database.
The variables entered into multivariable analyses were selected from those reported to have an association with DDE in previous studies [ 13].
The samples for analyses were selected from samples collected within the national bulk milk sampling scheme including samples from all Swedish dairy herds (approximate 7100 herds in 2007 [ 12]).
Participants included in these analyses were selected from a large multiethnic cohort (MEC) study in Hawaii and Los Angeles initiated with emphasis on diet and lifestyle characteristics in the aetiology of cancer.
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The gene expression data set used for these analyses was selected from a larger set that has been previously described [ 11].
Markers with P-value <0.001 (equivalent to controlling FDR at 25%) from both analyses were selected for further study.
Chain A from all analyses was selected for following structural analysis.
The cut-points for the 6MWD and Borg Scale [ 44] as used for the responsiveness and MID analyses were selected based on evidence from published literature.
The independent variables in the multiple regression analyses were selected based on results from earlier studies which show that age, sex, education level, marital status, BMD, falls, BMI, co-morbidity and osteoporotic fractures appear to be associated with HRQOL and/or GQOL, and these variables were all included in the regression model [ 14].
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