Strategy and tactics for graphic multiples in Stata
Many, perhaps most, useful graphs compare two or more sets of values. Examples are two or more groups or variables (as distributions, time series, etc.) or observed and fitted values for one or more model fits. Often there can be a fine line in such comparisons between richly detailed graphics and b...
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| Format: | Report |
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| Online Access: | http://repec.org/usug2013/cox.uk13.ppt http://repec.org/usug2013/njc_multiples.zip |
| Summary: | Many, perhaps most, useful graphs compare two or more sets of values. Examples are two or more groups or variables (as distributions, time series, etc.) or observed and fitted values for one or more model fits. Often there can be a fine line in such comparisons between richly detailed graphics and busy, unintelligible graphics that lead nowhere. In this presentation, I survey strategy and tactics for developing good graphic multiples in Stata. Details include the use of over() and by() options and graph combine; the relative merits of super(im)posing and juxtaposing; backdrops of context; killing the key or losing the legend if you can; transforming scales for easier comparison; annotations and self-explanatory markers; linear reference patterns; plotting both data and summaries; plotting different versions or reductions of the data. Datasets visited or revisited include James Short’s collation of observations from the transit of Venus; John Snow’s data on mortality in relation to water supply in London; Florence Nightingale’s data on deaths in the Crimea; deaths from the Titanic sinking; admissions to Berkeley; hostility in response to insult; and advances and retreats of East Antarctic ice sheet glaciers. Specific programs discussed include graph dot; graph bar; sparkline (SSC); qplot (SJ) and its relatives; devnplot (SSC); stripplot (SSC); and tabplot (SJ/SSC). |
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