S4 class for representing the statistical model

S4 class for representing the statistical model

Slots

mspec_file

modelspec file

main_effect

character string containing an independent variable whose effect you want to measure. It could be disease status, age, gender etc. This should strictly be a single variable. This can be either a categorical or a continuous variable.

covariates

character string containing a set of other predictors (variables) in the model. If more than one covariates are included, they should be separated by a + operator similar to an R formula.

corr_var

character variable name. This should be present in the demographics csv file associated with bstr_data.

corr_values

numeric vector to store correlation coefficients

corr_values_masked_adjusted

numeric vector storing the masked correlation coefficients corresponding to the adjusted p-values

group_var

Categorical variable name. This should be present in the demographics csv file associated with bstr_data.

model_type

character string denoting the type of model. Should be one of "bstr_anova", "bstr_corr", "bstr_corr", "pairedttest", "unpairedttest" or "bstr_lmer"

fullmodel

character string like an R formula denoting the full model including both the main effect and covariates.

nullmodel

character string like an R formula denoting the null model including covariates only

fullvars

character list of individual variables in the full model

nullvars

character list of individual variables in the null model

lm_formula

R formula()

X_design_full

a design matrix of the type model.matrix() for the full model

X_design_null

a design matrix of the type model.matrix() for the null model

Npfull

number of variables in the full model

Npnull

number of variables in the null model

unique

unique variable obtained as a setdiff(fullvars, nullvars)

pvalues

numeric vector storing the p-values

tvalues

numeric vector storing the t-statistics

tvalues_sign

numeric vector storing the sign of the t-statistics

Fstat

numeric vector storing the F-statistics

beta_coeff

numeric vector storing the beta coefficients

rss

numeric vector storing the residual sum of squares

residuals

numeric vector storing residuals # TODO: Check if this variable can be eliminated

se

numeric vector storing the standard error

mult_comp

character type of multiple comparison adjustment. Takes values of "fdr"

pvalues_adjusted

numeric vector storing the adjusted p-values

tvalues_adjusted

numeric vector storing the t-values corresponding to the adjusted p-values

stats_commands

list of R commands (primarily for ROI analysis)

load_data_command

character string for the command used to load the data