Your English writing platform
Discover LudwigSuggestions(5)
Exact(5)
Technically, nomograms use multiple logistic regression (MLR) to predict a binary outcome based on a combination of risk factors.
For illustrative purposes, this dataset was analyzed as a binary outcome, based on two year survival time.
Using the CHAT study dataset, we investigated the performance of different MI strategies for missing binary outcome based on MCAR and CD mechanisms.
Using this sample size, it was determined that it would be possible to detect a difference of 3.5% between two countries for a binary outcome (based on 90% compared with 93.5% for potential high adherence to recommendations, as anticipated for some process measures) with 80% power by a standard χ test (α = 5%).
For type 2 diabetes as a binary outcome, based on the 561 sib pairs (487 discordant and 74 concordant pairs), we had 20% power to detect an OR of 1.17 (the average European effect size) given MAF of 23% (average MAF in this study) (ESM Tables 2 and 3).
Similar(55)
A marginal logistic regression model for binary outcomes, based on generalised estimating equations, was used to generate the risk of reporting a particular 2-month period was associated with attacks of asthma (with January/February as the reference category).
LOS was changed into a binary summary outcome based on the median, i.e. ≤ or >11 days.
In the presence of a binary outcome, methods based on the receiver operating characteristic (ROC) curve are commonly and indistinctly used.
For the purpose of comparing continuous and binary outcome measures based on the same data, the HAQ 20 and HAQ 50 measures defined previously are estimated based on the continuous HAQ improvement.
This binary outcome was based on the cut-off score recommended in the HSCL-25 manual [ 34]; participants above the cut-off score of 1.75 were classified as cases i.e. those at risk of depression and anxiety.
Inferential contrasts for binary outcomes were based on odds ratios (OR; 95% CI) obtained from logistic regression models.
Write better and faster with AI suggestions while staying true to your unique style.
Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com