Monthly Archives: January 2013

analyze the medical expenditure panel survey (meps) with r

January 7, 2013
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the meps household component leads the pack for examining individual-level medical expenditures by payor and type of service.  total expenditures captured by the survey tend to be low, but unbiased across the board and can be adjusted to match the...

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Software Signals

January 7, 2013
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Software Signals

This blog post by Sean Taylor generated quite a stir. He discussed the signals one sends by using certain software packages and seems to think that R users are more competent. The reactions ranged from amusement to bashing. In defense of hard to learn statistical tools, i.e. #rstats prsm.tc/gyTBRK <- pretty funny 'who uses what I encourage you...

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Market predictions for year 2013

January 7, 2013
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Market predictions for year 2013

Calibrations of 2013 predictions for 18 equity indices — plus some publicly available predictions. Orientation The distributions are an attempt to see the variability if there were no market-driving news for the whole year. Another way of thinking: mentally moving the distribution to center on a prediction gives a sense of the variability of results … Continue reading...

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Using the Rcpp sugar function clamp

January 7, 2013
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Since the 0.10.* release series, Rcpp contains a new sugar function clamp which can be used to limit vectors to both a minimum and maximim value. This recent StackOverflow question permitted clamp to shine. We retake some of the answers, including the ...

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Internal Consistency Reliability in R with Lambda4

January 6, 2013
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For the last year I have been developing a package “Lambda4” to improve internal consistency reliability estimation.  In the package’s conception my primary concern centered on H.G. Osburn’s maximized lambda4 estimator.  Despite a very thorough search I could not find a stats package that could utilized Osburn’s method.  I wanted to learn R and so I jumped in and...

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Internal Consistency Reliability in R with Lambda4

January 6, 2013
By

For the last year I have been developing a package “Lambda4” to improve internal consistency reliability estimation.  In the package’s conception my primary concern centered on H.G. Osburn’s maximized lambda4 estimator.  Despite a very thorough search I could not find a stats package that could utilized Osburn’s method.  I wanted to learn R and so I jumped in and...

Read more »

Demonstrating Confidence Intervals with Shiny

January 6, 2013
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Demonstrating Confidence Intervals with Shiny

For the introductory statistic student confidence intervals can seem a daunting concept to grasp.  Quite simply put it is an interval that we have a certain measure of confidence that the population parameter falls into.  The 95% confidence is the most common value chosen in my academic circle.  Nevertheless, many others may be viable as well as long as...

Read more »

Demonstrating Confidence Intervals with Shiny

January 6, 2013
By
Demonstrating Confidence Intervals with Shiny

For the introductory statistic student confidence intervals can seem a daunting concept to grasp.  Quite simply put it is an interval that we have a certain measure of confidence that the population parameter falls into.  The 95% confidence is the most common value chosen in my academic circle.  Nevertheless, many others may be viable as well as long as...

Read more »

http://cran.r-project.org/web/packages/Lambda4/index.html

January 6, 2013
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http://cran.r-project.org/web/packages/Lambda4/index.html: Our own JackStat (Tyler) published his first package in R.

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http://cran.r-project.org/web/packages/Lambda4/index.html

January 6, 2013
By

http://cran.r-project.org/web/packages/Lambda4/index.html: Our own JackStat (Tyler) published his first package in R.

Read more »

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