strum (version 0.5.1)

createStrumModel: Create strumModel Object

Description

A function to create an object of class strumModel.

Usage

createStrumModel(formulas,
                 ascertainment = NULL,
                 defaultError = '',
                 assumeExogCovariate = TRUE,
                 fixLoadingToOne = TRUE)

Arguments

formulas

Vector of expressions that defines the relationship among the variables in the model (see Details).

ascertainment

Charactor stating the name of the column in data file that contains the indicator variable (1, 0) designating the probands of the pedigrees.

defaultError

Vector of chractor listing the default variance components in the model (see Details).

assumeExogCovariate

Logical. If TRUE, then it is assumed that any observed, quantitative exogenous traits are covariates. Otherwise, they are treated as latent and dependent variables.

fixLoadingToOne

Logical. If TRUE, then it sets the first indicator variable for each factor to have a coefficient of 1. Otherwise, all coefficients are estimated.

Value

• Returns an object of type strumModel.

Details

This function is used to create a trait model which will be an input parameter for strum function. The formulas argument is given as a charactor string of several expressions that defines the relationship among the variables. Blank lines and comments (line start with #) can be included between formulas. Three different equations are allowed in the formulas syntax:

1. Measurement equations The "=~" operator may be read as "measured by" and it specifies the measurement model equations in the model. The left hand side of the "=~" must contain one unobserved or latent factors. The right hand side of the "=~" are observed variables, observed covariates, and/or any measurement errors enclosed with "<>".
2. Structural equations The "~" operator specifies the structural equations in the model. The left hand side of the "~" must contain one unobserved or latent factor variable name. The right hand side of the "~" are unobserved or latent factors, observed covariates, and/or any random effects enclosed with "<>".
3. Adding a covariance By default, the endogenous error terms are uncorrelated, but the exogenous variables are correlated. To add a correlation between endogenous terms, use "cov" operator. For example,cov(x,y) = NA.
4. Removing a constraint on a coefficient By default, the value offixLoadingToOneequals TRUE, setting the first indicator variable for each factor to have a coefficient of 1. To disable this option selectively for a coefficient to be estimated, use "coef" operator. For example,coef(y1,z1) = NA.
5. Constraints The "=" operator specifies the constraints in the model, i.e., fixing a model parameter - fixed variance, fixed covariance, or fixed coefficient. The left hand side of the "=" must contain a reserved word for constraint - "var", "cov", or "coef" - with one or two variable names depending on the word. The right hand side of the "=" is a fixed value. Here are some examples:
   • Fixing the variance of a latent variable:var(stress) = .1
   • Fixing the covariance between two latent variables:cov(z1,z2) = 4
   • Fixing the coefficient between two variables:coef(y1,z1) = 2

If a random effect such as p, e, a or c is not included in the model formulas, then, by default, the value of defaultError is included in the model. For quantitative traits, the e term should always be present. Therefore, the program automatically include e term even if no error terms are specified either in formulas nor in defaultError. Note again that "a" (additive), "p" (polygenic), "c" (common environmental) and "e"(independent environmental) are reserved variable names to specify a type of variance component, so that may not be used as input arguments.

See Also

strumModel

Examples

# Model formulas.
#----------------
strumForm = 'bp     =~ SBP + DBP
             anger  =~ A1 + A2 + A3
             stress =~ S1 + S2 + S3
             bp ~ anger + stress + <p,e>
             stress ~ anger + rs6040343   
             var(stress)=.1  
            '

# Create a strumModel.
#---------------------
myStrumModel = createStrumModel(
                 formulas = strumForm,
                 ascertainment = "disease"
               )