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We selected samples from breast, colon and lung adenocarcinomas because large matched datasets were available for methylation, gene expression and copy number profiles.
As a consequence, four matched datasets were obtained from this process and used in the analyses: the Basque Country Dataset (BD), the Granada Dataset (GD), the Murcia Dataset (MD) and the Zaragoza Dataset (ZD).
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However, exactly matched datasets are difficult to gather, and such an approach relies on the assumption that the precise timing of expression change should be conserved.
Final analyses on the matched dataset were performed using a logistic regression with a random effect on the paired observations except for the length of stay analyzed with a Cox random effect model.
Results from the conditional logistic regression analyses using only the matched dataset were similar to the results obtained from the unconditional analyses that included the additional controls.
A secondary data analysis of the matched dataset was conducted.
The rest of the paper is organized in the following fashion: the LWF (firm-worker matched) dataset is described in Section 2 while Section 3 provides an empirical model of permanent layoffs which discusses the issue of selection due to firm survival.
When IPC identified an incident MRSA case from a screening specimen, the IPC-ProvLab matched dataset was able to find a clinical MRSA isolate within the year of the IPC case presentation.
The matched dataset was then used to conduct multiple regression analysis taking into account smoking (never/ever/ex), alcohol (never/ever/ex), BMI (subdivided as <18.5, 18.5 24.9, 25 29.9, 30 39.9) and current drug use (NSAID use, calcium supplements and bisphosphonate, duration subdivided into <30 days, and ≥30 days).
The average LNS for each matched dataset pair was calculated.
Then, meta-profiles that generate matched dataset have been used for the comparison of the expression profiles among studies using the "matching" approach.
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