Blog Archives

Luke-warm about micromaps

April 29, 2017
By
Luke-warm about micromaps

Continuing my exploring methods for spatial visualisation of data in R, today I’m looking at linked micromaps. Micromaps are a way of showing statistical graphics for a small subset of regions at a time, with a small map indicating which regions are...

Read more »

More cartograms of New Zealand census data (district and city level)!

April 24, 2017
By
More cartograms of New Zealand census data (district and city level)!

Just a short note to say that I’ve finished creating an experimental map of New Zealand by the 66 Territorial Authorities (districts and cities), with area expanded or shrunk to be proportional to population at the 2013 census. This is in addition t...

Read more »

Cartograms of New Zealand census data

April 22, 2017
By
Cartograms of New Zealand census data

I’ve been trying to catch up with mapping functionality in R and its extended ecoverse, so might do a few posts on this in the next month or so. First up (more or less by accident) is cartograms - maps where some other numeric variable is substitut...

Read more »

Impact of omitted variables on estimating causal effects – simulations

April 14, 2017
By
Impact of omitted variables on estimating causal effects – simulations

The story so far Last week I looked at a few related methods of investigating causality with observational data, where the treatment is expected to be received by observational units (people or firms)… in a way that is structurally related to ...

Read more »

Exploring propensity score matching and weighting

April 8, 2017
By
Exploring propensity score matching and weighting

This post jots down some playing around with the pros, cons and limits of propensity score matching or weighting for causal social science research. Intro to propensity score matching One is often faced with an analytical question about causality and effect sizes when the only data around is from a quasi-experiment, not the random controlled trial one would hope for....

Read more »

New Zealand election forecasts

March 25, 2017
By
New Zealand election forecasts

Over the weekend I released a new webpage, connected to this blog, with forecasts for the New Zealand 2017 General Election. The aim is to go beyond poll aggregation to something that takes the uncertainty of the future into account, as well as relati...

Read more »

House effects in New Zealand voting intention polls

March 20, 2017
By
House effects in New Zealand voting intention polls

This post is one of a series leading up to a purely data-driven probabilistic prediction model for the New Zealand general election in 2017. No punditry will be indulged in (if only to avoid complications with my weekday role as an apolitical public s...

Read more »

Simulations to explore excessive lagged X variables in time series modelling

March 11, 2017
By
Simulations to explore excessive lagged X variables in time series modelling

I was once in a meeting discussing a time series modelling and forecasting challenge where it was suggested that “the beauty of regression is you just add in more variables and more lags of variables and try the combinations until you get something that fits really well”. Well, no, it doesn’t work like that; at least not in...

Read more »

New data and functions in nzelect 0.3.0 R package

March 10, 2017
By
New data and functions in nzelect 0.3.0 R package

Polling data and other goodies ready for download A new version, 0.3.0, of the nzelect R package is now available on CRAN. historical polling data from 2002 to February 2017, sourced from Wikipedia some small functions to help convert voting numb...

Read more »

Visualising relationships between children’s books

March 3, 2017
By
Visualising relationships between children’s books

At the OZCOTS (Australian Conference on Teaching Statistics) in late 2016 George Cobb gave a great talk entitled “Ask not what data science can do for the Humanities. Ask rather, what the Humanities can do for data science.” “George Cobb of M...

Read more »

Sponsors

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)