Weighted Gower's dissimilarity measure (Trials' comparability for transitivity evaluation)
Source:R/gower.distance_function.R
gower_distance.Rdgower_distance calculate the weighted Gower's dissimilarity
coefficient for all pairs of trials included in a network of interventions,
considering several characteristics measured at trial level.
It takes values from 0 to 1, with 0 implying complete similarity and 1
complete dissimilarity.
Arguments
- input
A data-frame in the long arm-based format. Two-arm trials occupy one row in the data-frame. Multi-arm trials occupy as many rows as the number of possible comparisons among the interventions. The first two columns refer to the trial name, and the pairwise comparison, respectively. The remaining columns refer to summary characteristics. See 'Details' for the specification of the columns.
- weight
A vector of non-negative numbers to define the weight contribution of each characteristic. The default is a vector of 1s for all characteristics.
Value
gower_distance returns the following list of elements:
- Dissimilarity_table
A lower off-diagonal matrix of 'dist' class with the dissimilarities of all pairs of trials.
- Types_used
A data-frame with type mode (i.e., double or integer) of each characteristic.
- Total_missing
The percentage of missing cases in the comparison, calculated as the ratio of total missing cases to the product of the number of studies with the number of characteristics.
Details
The correct type mode of columns in input must be ensured to use
the function gower_distance. The first two columns referring to
the trial name, and pairwise comparison, respectively, must
be character. The remaining columns referring to the
characteristics must be double or integer depending on
whether the corresponding characteristic refers to a quantitative or
qualitative variable. The type mode of each column is assessed by
gower_distance using the base function typeof. Note that
gower_distance invites unordered and ordered variables; for the
latter, add the argument ordered = TRUE in the base function
factor().
gower_distance is integrated in the function
comp_clustering.
References
Gower J. General Coefficient of Similarity and Some of Its Properties. Biometrics 1971;27(4):857–71. doi: 10.2307/2528823