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The Mincer earnings function is a single-equation model that explains wage income as a function of schooling and experience. It is named after Jacob Mincer. [1] [2] Thomas Lemieux argues it is "one of the most widely used models in empirical economics". The equation has been examined on many datasets.
Diabetes 130-US hospitals for years 1999–2008 Dataset 9 years of readmission data across 130 US hospitals for patients with diabetes. Many features of each readmission are given. 100,000 Text Classification, clustering 2014 [275] [276] J. Clore et al. Diabetic Retinopathy Debrecen Dataset
The OECD (Organization for Economic Co-operation and Development) dataset contains data on average annual wages for full-time and full-year equivalent employees in the total economy. Average annual wages per full-time equivalent dependent employee are obtained by dividing the national-accounts-based total wage bill by the average number of ...
Salary Survey; Salary in Germany; Eurostat: Wages and labour costs; Eurostat: Minimum wages August 2011; FedEE;Pay in Europe 2010; Wages (statutory minimum, average monthly gross, net) and labour cost (2005) CE Europe; Wages and Taxes for the Average Joe in the EU 27 2009; Moldovans have lowest wages in Europe; UK Net Salary Calculator
Since the 1990s, CEO compensation in the U.S. has outpaced corporate profits, economic growth and the average compensation of all workers. Between 1980 and 2004, Mutual Fund founder John Bogle estimates total CEO compensation grew 8.5 per cent/year compared to corporate profit growth of 2.9 per cent/year and per capita income growth of 3.1 per cent.
In the first dataset, two persons (1, 2) are observed every year for three years (2016, 2017, 2018). In the second dataset, three persons (1, 2, 3) are observed two times (person 1), three times (person 2), and one time (person 3), respectively, over three years (2016, 2017, 2018); in particular, person 1 is not observed in year 2018 and person ...
In current usage, the "reporting year" after the term "HEDIS" is one year following the year reflected in the data; for example, the "HEDIS 2009" reports, available in June 2009, contain analyses of data collected from "measurement year" January–December 2008. [4]
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]