Nothing

```
createDataTypes <- function(formula, whichRandom, data, analysis){
factors <- rownames(attr(terms(formula, data = data),"factors"))[-1]
factors <- unlist(decomposeTerms(factors))
cnames <- colnames(data)
# check status of data columns
types = sapply(cnames, function(name, data){
ifelse(is.factor(data[,name]), "fixed", "continuous")
}, data = data)
# restrict to only columns of interest
types = types[ names(types) %in% factors ]
if(length(types) <1 ) return(c())
if( any(types[ names(types) %in% whichRandom ] == "continuous") )
stop("Nonfactors are specified as random.")
if(length(whichRandom)>0)
types[ names(types) %in% whichRandom ] = "random"
#### check various analysis types
## ANOVA can only accept factors
if( any(types=="continuous") & analysis == "anova" )
stop("anovaBF() cannot be used with nonfactor independent variables. Use lmBF(), regressionBF(), or generalTestBF() instead.")
## regression can only accept nonfactors
if( any(types %in% c("fixed", "random")) & analysis == "regression" )
stop("regressionBF() cannot be used with factor independent variables. Use lmBF(), anovaBF(), or generalTestBF() instead.")
#### End checking analysis types
return(types)
}
checkFormula <- function(formula, data, analysis){
if(length(formula) < 3) stop("LHS of formula must be given.")
cnames = colnames(data)
dv = stringFromFormula(formula[[2]])
if(!is.numeric(data[,dv])) stop("Dependent variable must be numeric.")
if(any(is.na(data[,dv])) | any(is.infinite(data[,dv]))) stop("Dependent variable must not contain missing or infinite values.")
factors = fmlaFactors(formula, data)
terms = colnames(attr(terms(formula, data = data),"factors"))
decom = decomposeTerms(terms)
terms = unlist(decom)
vars = rownames(attr(terms(formula, data = data),"factors"))
vars = unlist(decomposeTerms(vars))
if(any(is.na(data[,vars]))) stop("Predictors must not contain missing values.")
if(is.null(factors)) return()
if(factors[1] %in% terms) stop("Dependent variable cannot be a predictor.")
if(!all(factors %in% cnames)) stop("Some variables missing in data frame.")
if(analysis=="regression"){
RHS = stringFromFormula(formula[[3]])
lengths = sapply(decom, length)
if (any(lengths > 1)) stop("Interactions not allowed in regressionBF (try generalTestBF).")
}
if(analysis=="lm" | analysis=="anova" | analysis == "regression" | analysis == "indept")
if(attr(terms(formula, data = data),"intercept") == 0) stop("Formula must include intercept.")
if(analysis=="indept"){
if( length(decom) > 1 ) stop("Indep. groups t test can only support 1 factor as predictor.")
if(length(decom[[1]]) > 1) stop("Interaction terms are not allowed in t test.")
if(nlevels(factor(data[,terms])) > 2) stop("Indep. groups t test requires a factor with exactly 2 levels.")
}
invisible()
}
checkEffects <- function(effects, data, dataTypes){
if(!all(effects %in% colnames(data))) stop("Term in formula missing in data")
if(!all(effects %in% names(dataTypes))) stop("Term in formula missing in dataTypes")
# add more checking code here
# most importantly, to check consistancy of data factors and dataTypes
# no factors should be labeled as continuous, etc
}
```

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