Articles by Andrés Gutiérrez

Scatter plots in survey sampling

November 27, 2017 | 0 Comments

You can find this post in Blogdown format by clicking hereWhen it comes to analyzing survey data, you have to take into account the stochastic structure of the sample that was selected to obtain the data. Plots and graphics should not be an exception. ...
[Read more...]

dplyr and the design effect in survey samples

November 21, 2017 | 0 Comments

Blogdown entry here.For those guys like me who are not such R geeks, this trick could be of interest. The package dplyr can be very useful when it comes to data manipulation and you can extract valuable information from a data frame. For example, when ... [Read more...]

Automatic output format in Rmarkdown

November 19, 2017 | 0 Comments

I am writing a Rmarkdown document with plenty of tables, and I want them in a decent format, e.g. kable. However I don't want to format them one by one. For example, I have created the following data frame in dplyrdata2 %__% group_by(uf) %__% sum...
[Read more...]

Sampling weights and multilevel modeling in R

June 15, 2017 | 0 Comments

So many things have been said about weighting, but on my personal view of statistical inference processes, you do have to weight. From a single statistic until a complex model, you have to weight, because of the probability measure that induces the var... [Read more...]

Small Area Estimation 101

April 16, 2017 | 0 Comments

Small area estimation (SAE) has become a widely used technique in official statistics since the last decade of past century. When the sample size is not enough to provide reliable estimates at a very particular level, the power of models and auxiliary ... [Read more...]

Gelman’s MrP in R – What is this all about?

January 15, 2017 | 0 Comments

Multilevel regression with poststratification (MrP) is a useful technique to predict a parameter of interest within small domains through modeling the mean of the variable of interest conditional on poststratification counts. This method (or methods) w... [Read more...]

Computing Sample Size for Variance Estimation

December 24, 2016 | 0 Comments

The R package samplesize4surveys contains functions that allow to calculate sample sizes for estimating proportions, means, difference of proportions and even difference of two means. It also permits the calculation of sample error and power level for ...
[Read more...]

Highlighting R code for the web

December 3, 2016 | 0 Comments

When blogging about statistics and R, it is very useful to differentiate the body text to R code. I used to manage this issue by highlighting the code and pretty-R was a valuable instrument from Revolutions Analytics to accomplish this. However, as you... [Read more...]

How important is that variable?

December 3, 2016 | 0 Comments

When modeling any phenomena by including explanatory variables that highly relates the variable of interest, one question arises: which of the auxiliary variables have a higher influence on the response? I am not writing about significance testing or s... [Read more...]

Lord’s Paradox in R

November 20, 2016 | 0 Comments

In an article called A Paradox in the Interpretation of Group Comparisons published in Psychological Bulletin, Lord (1967) made famous the following controversial story:A university is interested in investigating the effects of the nutritional diet its...
[Read more...]

Sublime Text 3: an alternative to RStudio

October 17, 2016 | 0 Comments

It was a Saturday morning; I was lecturing my students of my Item Response Theory class when I decided to run some R scripts to introduce my students with the JAGS syntax and the estimation of parameters in a Bayesian logistic regression setup.As it wa...
[Read more...]

Multilevel Modeling of Educational Data using R (Part 1)

October 11, 2016 | 0 Comments

Linear models fail to recognize the effect of clustering due to intraclass correlation accurately. However, under some scenarios force you to take into account that units are clustered into subgroups that at the same time are nested within larger group...
[Read more...]

Isolating confounding effects – Rankings and residuals

July 8, 2016 | 0 Comments

In a previous entry, we talked about the meaning and importance of isolating confounding variables. This entry is dedicated to the residuals and its relation to the variable of interest when controlling for some confounding factors.Let's think about ed...
[Read more...]

I don’t care about that lost unit

June 4, 2016 | 0 Comments

Just assume that you have planned a survey along with the necessary sample size to obtain representativity. Let’s suppose the sample size is 100. However, as nonresponse is always present, unfortunately your effective sample size is 99. Consider the...
[Read more...]

IRT classic anchoring with R functions

March 16, 2016 | 0 Comments

The main goal of standardised tests is to produce scores that can be compared not only within subgroups of students (and subpopulations of interest) but between applications (in different times). In summary, researchers and methodologists must assure t...
[Read more...]

Parametric bootstrap

August 7, 2015 | 0 Comments

Assume we want to know the mean square error (MSE) of the sample median as a estimator of a population mean under normality. As you know, this is not a trivial problem. We may take advantage of the Bootstrap method and solve it by means of simulation.... [Read more...]

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)