Merge pull request #41 from dustinfife/development

Merge JASP/jamovi developments into master

Author: dustinfife

.DS_Store

@@ -6,6 +6,7 @@
 ^\.git$     
 jamovi
 .travis.yml
+flexplot.svg
 ^build$
 ^icon.svg$
 ^flexplot.jmo$
@@ -18,9 +19,19 @@ tests/
 ^Meta$
 EJ notes.rtf
 R/flexplota.b.R
+# stuff to ignore jasp when doing CMD check
+R/glinmod_jasp.R
+R/linmod_jasp.R
+R/flexplot_jasp2.R
+R/mixedmod_jasp.R
+R/jasp_common.R
+
 R/flexplota.h.R
 R/glmbasic.b.R
 R/glmbasic.h.R
 R/modelcomp.b.R
 R/modelcomp.h.R
-vignettes/regex_syntax.txt
+R/scratch/
+data/generate_data.R
+vignettes/regex_syntax.txt
+vignettes/psychmethods/

.Rbuildignore

@@ -1,7 +1,7 @@
 Package: flexplot
 Type: Package
 Title: Graphically Based Data Analysis Using Flexplot
-Version: 0.6.7
+Version: 0.7.2
 Author: Dustin Fife
 Maintainer: Dustin Fife <[email protected]>
 Description: The ‘flexplot’ suite is a graphically-based set of tools for doing data analysis. flexplot() allows users to specify a formula and the software automatically chooses what sort of graphic to present. Analysis can be paired with visuals using the visualize() function, such that the software will choose an appropriate graphic to match an R model object.

DESCRIPTION

@@ -14,15 +14,11 @@ export(bf.bic)
 export(compare.fits)
 export(estimates)
 export(flexplot)
-export(flexplot_jasp2)
 export(flip_data)
 export(geom_jitterd)
 export(glinmod)
-export(glinmod_jasp)
-export(linmod_jasp)
 export(make.formula)
 export(mixed.mod.visual)
-export(mixedmod_jasp)
 export(model.comparison)
 export(position_jitterd)
 export(position_jitterdodged)

NAMESPACE

@@ -46,11 +46,6 @@ compare.fits = function(formula, data, model1, model2=NULL, return.preds=F, repo
     outcome = variables[1]
     predictors = variables[-1]
 
-    #### for the rare occasion where deleting missing data changes the levels...
-    if (length(predict(model1))<nrow(data) | length(predict(model2))<nrow(data)){
-      data = na.omit(data[,variables])
-    }    
-    
     ##### make sure they're putting the same variables from formula in terms
 	if (!(all(predictors %in% testme))){
 		stop(paste0("Sorry, but some variables in formula don't match what's in the model. Specifically: ", paste0(variables[!(variables%in%terms.mod1)], collapse=",")))
@@ -61,8 +56,12 @@ compare.fits = function(formula, data, model1, model2=NULL, return.preds=F, repo
 		stop(paste0("Sorry, but some variables in formula don't match what's in the dataset. Specifically: ", paste0(variables[!(variables%in%data)], collapse=","), ". Did you input the wrong dataset?"))
 	}	
 
-
-	#### create random column just to make the applies work (yeah, it's hacky, but it works)
+    #### for the rare occasion where deleting missing data changes the levels...
+    if (length(predict(model1))<nrow(data) | length(predict(model2))<nrow(data)){
+      data = na.omit(data[,variables])
+    }    
+    
+	  #### create random column just to make the applies work (yeah, it's hacky, but it works)
     data$reject = 1:nrow(data); data$reject2 = 1:nrow(data)
     predictors = c(predictors, "reject", "reject2")
 

R/compare.fits.R

@@ -1,3 +1,26 @@
+#' Simulated Statistics on the Final Avengers Battle
+#'
+#' A dataset containing combat attributes of almost 812 
+#' fighters in the final Avengers battle
+#'
+#' @format A data frame with 812 rows and 13 variables:
+#' \describe{
+#'   \item{iq}{Intelligence}
+#'   \item{agility}{weighted scores on an obstacle course}
+#'   \item{speed}{Speed in running the 40 meter dash}
+#'   \item{strength}{Pounds lifted in a benchpress}
+#'   \item{damage.resistence}{Amount of skin deflection (in mm) when slapped with a frozen fish}
+#'   \item{flexibility}{Number of inches past their toes they can reach}
+#'   \item{willpower}{Length of time they wait at a DMV for a driver's license}
+#'   \item{superpower}{Does this person have a superpower?}   
+#'   \item{died}{Whether the person died at the final battle}
+#'   \item{kills}{Number of enemies killed in the final battle}
+#'   \item{injuries}{Number of injuries sustained. Anything more than 5 is marked as a 5}
+#'   \item{minutes.fighting}{Number of minutes spent fighting before dying or giving up}
+#'   \item{shots.taken}{Number of shots (with a gun) or punches thrown at an enemy}
+#' }
+"avengers"
+
 #' Alcohol use among youth
 #'
 #' A dataset containing alcohol use from 82 youth over the course of three years

R/data_documentation.R

@@ -2,18 +2,20 @@
 #'
 #' Report object Estimates
 #' @param object a object
+#' @param mc Should model comparisons be performed?
 #' @export
-estimates = function(object){
+estimates = function(object, mc=TRUE){
 	UseMethod("estimates")
 }
 
 #' Output APA style statistical significance from an object 
 #'
 #' Output APA style statistical significance from an object
 #' @param object a object
+#' @param mc Should model comparisons be performed?
 #' @return One or more objects containing parameter estimates and effect sizes
 #' @export
-estimates.default = function(object){
+estimates.default = function(object, mc=TRUE){
 	out = summary(object)
 	class(out) = "estimates"
 	out
@@ -23,9 +25,10 @@ estimates.default = function(object){
 #'
 #' Report lm object Estimates
 #' @param object a lm object
+#' @param mc Should model comparisons be performed?
 #' @return One or more objects containing parameter estimates and effect sizes
 #' @export
-estimates.lm = function(object){
+estimates.lm = function(object, mc=TRUE){
 
 	n = nrow(model.frame(object)) 
 
@@ -43,7 +46,7 @@ estimates.lm = function(object){
 	}
 	#### get dataset
 	d = object$model
-  dataset=NULL
+  #}dataset=NULL
 	#### identify factors
 	if (length(terms)>1){
 		### convert characters to factors
@@ -213,8 +216,7 @@ estimates.lm = function(object){
 	}
 
 	### do nested model comparisons
-	if (length(terms)>1){
-	  #save(object, terms, file="/Users/fife/Dropbox/jaspResults.Rdat")
+	if (length(terms)>1 & mc){
 	  removed.one.at.a.time = function(i, terms, object){
 	    new.f = as.formula(paste0(". ~ . -", terms[i]))
 	    new.object = update(object, new.f)
@@ -224,7 +226,7 @@ estimates.lm = function(object){
 	    )
 	  }
 	  ### this requires superassignment to work with JASP
-	  dataset<<-object$model
+	  #dataset<<-object$model
 	  all.terms = attr(terms(object), "term.labels")
 	  mc = t(sapply(1:length(all.terms), removed.one.at.a.time, terms=all.terms, object=object))
 	  mc = data.frame(cbind(all.terms,mc), stringsAsFactors = FALSE)
@@ -262,9 +264,10 @@ estimates.lm = function(object){
 #'
 #' Report glm object Estimates
 #' @param object a glm object
+#' @param mc Should model comparisons be performed? Currently not used
 #' @return One or more objects containing parameter estimates and effect sizes
 #' @export
-estimates.glm = function(object){
+estimates.glm = function(object, mc=FALSE){
 	#### generate list of coefficients
 	terms = attr(terms(object), "term.labels")
 
@@ -332,8 +335,9 @@ estimates.glm = function(object){
 #'
 #' Report zeroinfl object Estimates
 #' @param object a zeroinfl object
+#' @param mc Should model comparisons be performed? Currently not used
 #' @export
-estimates.zeroinfl = function(object){
+estimates.zeroinfl = function(object, mc=FALSE){
 
 	#### get dataset
 	d = object$model