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To calculate national estimates for influenza pneumonia hospitalization, we extrapolated population-based data that captured all pneumonia admissions from our two study provinces (population 1.2 million) under the assumption that the incidence of hospitalized influenza pneumonia does not differ systematically year after year across the 76 provinces of Thailand.
Codes were meaningful groups of data that captured the essence of the data.
Codes were meaningful groups of data that captured the essence of data and could be events (e.g. hypoglycaemia: night-time), emotions (e.g. hypoglycaemia: parental concern) or beliefs (e.g. hypoglycaemia: very challenging).
This paper presents a secondary analysis of qualitative data that captured the experiences of men who engaged with a national government programme that was aimed at improving men's health in Scotland.
For example, one might suggest that ideal multipollutant categories in this setting would reflect cutpoints in the data that captured homogeneous risk within categories and heterogeneous risk between categories.
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Yet a simple supplementary index can be calculated from readily available data that captures one of the most important ways that changing distribution patterns have affected middle-income families.
Studies over the past years have also accumulated data that captures the physiological behavior of the NUs and their divergence in abiotic stress responses (Yamamoto et al. 2011; Atayese et al., 2016; Sikuku et al. 2012; Sakariyawo et al. 2015).
One of the reasons for the lack of research in these countries is the lack of labor data that captures the earnings, tenure, and separations information required for dynamic monopsony estimation.
However, there are little data on the developmental and behavioral problems experienced by children living with epilepsy, especially qualitative data that capture community perceptions of the challenges faced by these children.
The sum-of-Conway-Maxwell-Poissons (sCMP) class of distributions is a flexible construct for modeling count data that captures several well-known distributions as special cases: the Poisson, negative binomial, binomial, geometric, Bernoulli, and Conway-Maxwell-Poisson (CMP).
In this approach, rather than focusing on the development of a kinetic model that fits the dynamic metabolite concentration data, we seek to utilize data that captures the effect of enzyme tuning on the steady state production flux to guide model development.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com