- fix documentation for package (adding missing alias required by CRAN, and bring pkg doc page up to date)
- add forest plot
show.bootstraps
defaults toTRUE
only if fewer than 100,000 observations- fix bug in intercept-only models where upper CI was missing
- add marginal model plots (from 'car') which are useful for
glm
objects
- refactor plots using ggplot creating new method for
inzplot
(from iNZightPlots) - removes some functions that aren't used by iNZightRegression, and are available in iNZightMR instead
- add column for exponentiated estimates where appropriate
- add
exponentiate.cis
argument toiNZightSummary
which replaces the CIs with exponentiated versions if appropriate (FALSE
by default) - factorComp() for survey GLMs includes Wald test for term effects (regTermTest())
- add summary method for Cox PH models
Release date: 21 April 2020
- specify
stringsAsFactors = TRUE
for upcoming R 4.0.0 - fix bug in processing summary for models with
exlude
d variables
Release date: 11 November 2019
- fix bug in regression summary causing interactions to fail
Release date: 2 September 2019
- add parameter confidence limits to regression summary output
- add model comparison function (AIC, BIC)
- add
factorComp()
function to obtain adjusted pairwise comparisons of factor levels in a model
Release date: 15 July 2019
- disable smoother for intercept-only models (
y ~ 1
) - fix some issues with bootstrapping
Release date: 30 April 2019
- display link function used in binomial regression fits
- suppress warnings from
loess()
calls
Release date: 01 February 2019
- fix bug where residual plot for null model was painfully slow to draw
Release date: 15 November 2018
- display baseline level for binary GLMs
Release date: 02 October 2017
- fix bootstrapping algorithm
- summary of model with only confounding variables (i.e., "adjusted intercept")
Release date: 25 August 2017
- remove NAs from qq-plot abline
Release date: 23 August 2017
This isn't a hugely updated version, however fixing up a bunch of bugs
to make the Model Fitting module better (over on iNZightModules
).
- export a
Poly()
function, which is just apoly()
function that supportsNA
s
- catch errors in model bootstrapping so the rest of the plot still works
- use the
subset
argument tolm
(viaupdate()
) to perform bootstraps, rather than the long-winded data-bootstrapping call-modifying version that was buggy - fix up bootstrapping algorithms for QQ-plot and histogram arrays
Release date: 18 August 2017
- various fixes, package maintenance
Release date: 23 March 2017
- fix bootstrapping method for linear models
Release date: 9 January 2017
- fix a bug preventing plots from drawing when provided a
glm
object
Release date: 20 July 2015
- Adds an extra argument
use.inzightplots
to the plotting functions that allows users to enable/disable the use of them as desired. Currently, the default isFALSE
as the latest version ofiNZightPlots
is incompatible withiNZightRegression
.
- added missed function and method exports
Release date: 17 September 2014
- on some graphics devices (e.g., RStudio)
grid.rect()
is not transparent; now enforces these to be transparent
Release date: 4 April 2014
- Continuing on from previous update, the partial residual
plots are now modified to make use of the
iNZightPlots
library if it is installed.
Release date: 27 March 2014
-
Residual summary plots from
plotlm6
can now make use of theiNZightPlots
graphics rather than the defaults. It requires the user to haveiNZightPlots
installed to work, but reverts to the old plots if it is not. -
In the new
grid
based plots, quantile smoothers are used rather than loess smoothers. This greatly increases efficiency when large data sets are analysed.
-
Maximum sample size for drawing bootstraps implemented (currently at 4000), as over this they don't provide much information (this can be overridden by
showBootstraps = TRUE
). -
P-values for normality test are printed as "P < 0.001" rather than "P = 0".
- Shapiro-Wilk test not used if sample size > 5000 (resulted in an error).
Release date: 18 January 2014
-
Support for generalized linear models (GLMs) and
svyglm
objects from thesurvey
package. -
Changes to the
iNZightSummary
output include:-
Output now hides output of confounding variables through the
exclude
argument, and lists these at the top of the output. -
Displays the type of fit (e.g., Survey / Generalized Linear / Model).
-
-
The QQ-plot array has been replaced by a single plot with the parametric bootstrap data QQ-plots all on a single plot, overlaid by the QQ-plot of the true data (this was suggested by Thomas Lumley).
- The Histogram Array has been rewritten using
grid
, and minimizes margin whitespace and draws simulated histograms in a different colour.
-
The bootstrap models functions have been re-written to account for the
design
option in survey GLMs, as well as the case when the GLM binomial response is SUCCESS / N.TRIALS. This caused errors in thefit$model
that was previously being used. -
The bootstrap lines from
plotlm6
have been fixed so that they now work for(svy)glm
objects. There is also an optional cut-off if the sample size becomes too small (which can be overridden by theshowBootstraps = TRUE|FALSE
argument. -
factorMeans
andadjustedMeans
have been enhanced to work with GLMs.
- Initial support for generalized linear models (GLMs),
including the
survey
package'ssvyglm
.
-
First release of new package. Contains model fitting subset used for the
iNZight
package. -
Added
histogramArray
andqqplotArray
plots to show how residuals from a model compare to the residuals generated from that model. -
New margin of error calculation functions. Initially written by Danny Chang. Used for comparison between levels of a factor.
moecalc
has a few standard methods that can be used:print
,plot
, andsummary
. In addition, amulticomp
method has been added which is a useful tabulation of multiple comparison output. Note however withmulticomp
that the p-values are currently unadjusted. -
New summary output,
iNZightSummary
. Includes several Changes compared to the R-base model summary output. These include the following:-
Now showing the factor itself in the output, not just rows for coefficients for levels of the factor.
-
When a factor is included in a model, the summary output will show the name of the factor and show the p-value for the factor (based on Type-III sums of squares). This p-value is not affected by further use of the factor (i.e. in an interaction). Sometimes this p-value cannot be calculated (i.e. when there are unobserved factor level combinations) and the p-value will be omitted.
-
The baseline level of a factor is now shown, with an estimate of 0.
-
All p-value output for levels of a factor is indented to the right by two characters to distinguish it from being a level.
-
The output for each factor level is now just the level name and not the name of the variable concatenated with the level name. The level name is also indented by two characters, again to distinguish it from the variable itself.
-
Removing F-statistic and associated p-value as it's mostly useless. It only shows us whether nothing is correlated with the response variable, i.e. whether we're completely wasting our time.
-
Removed model call output and residual output. Replaced with "Model for:" (plus response name).
-
-
Added a new
plot.lm
function. The main difference being that it includes bootstrapped smoothers in its output as well as the regular trend lines. Also includes plots based on thes20x
package'snormcheck
function. -
Added partial residual plots. Most useful for determining whether the inclusion of a transformation of a variable is necessary. For example, adding a logged or polynomial explanatory variable to the model.
-
Adding bootstrapped estimates to
iNZightSummary
. Accessed by calling the function withmethod="bootstrap"
.
- Using
loess
for smoothers instead oflowess
(newer and more robust).