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You are here		www.econometricsbysimulation.com Econometrics By Simulation: Easily generate correlated variables from any distribution
\|	\|	rpsychologist.com Estimating treatment effects and ICCs from (G)LMMs on the observed scale using Bayes, Part 1: lognormal models \| R Psychologist	4.0 parsecs away Travel
\|	\|	When a multilevel model includes either a non-linear transformation (such as the log-transformation) of the response variable, or of the expectations via a...	4.0 parsecs away Travel
\|	\|	andrewpwheeler.com Group based trajectory models in Stata - some graphs and fit statistics \| Andrew Wheeler	1.9 parsecs away Travel
\|	\|	For my advanced research design course this semester I have been providing code snippets in Stata and R. This is the first time I've really sat down and programmed extensively in Stata, and this is a followup to produce some of the same plots and model fit statistics for group based trajectory statistics as this...	1.9 parsecs away Travel
\|	\|	www.huber.embl.de Modern Statistics for Modern Biology - 4 Mixture Models	1.7 parsecs away Travel
\|	\|	If you are a biologist and want to get the best out of the powerful methods of modern computational statistics, this is your book.	1.7 parsecs away Travel
\|	\|	teddykoker.com Multi-Class Classification with Logistic Regression in Python \| Teddy Koker	50.8 parsecs away Travel
\|		A few posts back I wrote about a common parameter optimization method known as Gradient Ascent. In this post we will see how a similar method can be used to create a model that can classify data. This time, instead of using gradient ascent to maximize a reward function, we will use gradient descent to minimize a cost function. Lets start by importing all the libraries we need:	50.8 parsecs away Travel