Extract regression coefficient values

Question

I have a regression model for some time series data investigating drug utilisation  The purpose is to fit a spline to a time series and work out 95  CI etc  The model goes as follows   id  lt - ts 1 length drug Date   a1  lt - ts drug Rate  a2  lt - lag a1-1  tg  lt - ts union a1 id a2  mg  lt -lm  a1 a2 bs id df df1  data tg     The summary output of mg is   Call  lm formula   a1   a2   bs id  df   df1   data   tg   Residuals       Min       1Q   Median       3Q      Max  -0 31617 -0 11711 -0 02897  0 12330  0 40442   Coefficients                    Estimate Std  Error t value Pr  gt  t        Intercept         0 77443    0 09011   8 594 1 10e-11     a2                 0 13270    0 13593   0 976  0 33329     bs id  df   df1 1 -0 16349    0 23431  -0 698  0 48832     bs id  df   df1 2  0 63013    0 19362   3 254  0 00196     bs id  df   df1 3  0 33859    0 14399   2 351  0 02238     --- Signif  codes   0       0 001      0 01     0 05     0 1     1    I am using the Pr  gt  t   value of a2 to test if the data under investigation are autocorrelated   Is it possible to extract this value of Pr  gt  t    in this model 0 33329  and store it in a scalar to perform a logical test   Alternatively  can it be worked out using another method

User · Answer

The package broom comes in handy here  it uses the  tidy  format    tidy mg  will give a nicely formated data frame with coefficients  t statistics etc  Works also for other models  e g  plm         Example from broom s github repo   lmfit  lt - lm mpg   wt  mtcars  require broom      tidy lmfit         term estimate std error statistic   p value 1  Intercept    37 285   1 8776    19 858 8 242e-19 2          wt   -5 344   0 5591    -9 559 1 294e-10  is data frame tidy lmfit    1  TRUE

User · Answer

A summary lm object stores these values in a matrix called  coefficients   So the value you are after can be accessed with    a2Pval  lt - summary mg  coefficients 2  4    Or  more generally readably  coef summary mg    a2   Pr  gt  t      See here for why this method is preferred

User · Answer

Just pass your regression model into the following function       plot coeffs  lt - function mlr model          coeffs  lt - coefficients mlr model        mp  lt - barplot coeffs  col   3F97D0   xaxt  n   main  Regression Coefficients         lablist  lt - names coeffs        text mp  par  usr   3   labels   lablist  srt   45  adj   c 1 1 1 1   xpd   TRUE  cex 0 6          Use as follows   model  lt - lm Petal Width      data   iris   plot coeffs model

User · Answer

To answer your question  you can explore the contents of the model s output by saving the model as a variable and clicking on it in the environment window  You can then click around to see what it contains and what is stored where   Another way is to type yourmodelname  and select the components of the model one by one to see what each contains  When you get to yourmodelname coefficients  you will see all of beta-  p  and t- values you desire

[r] Extract regression coefficient values

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