Calculate Coefficient of Dispersion (COD)

Source: R/formulas.R, R/ci.R

COD is the average absolute percent deviation from the median ratio. It is a measure of horizontal equity in assessment. Horizontal equity means properties with a similar fair market value should be similarly assessed.

Lower COD indicates higher uniformity/horizontal equity in assessment. The IAAO sets uniformity standards that define generally accepted ranges for COD depending on property class. See IAAO Standard on Ratio Studies Section 9.1, Table 1.3 for a full list of standard COD ranges.

NOTE: The IAAO recommends trimming outlier ratios before calculating COD, as it is extremely sensitive to large outliers. The typical method used is dropping values beyond 3 * IQR (inner-quartile range). See IAAO Standard on Ratio Studies Appendix B.1.

cod(ratio, na.rm = FALSE)

cod_ci(ratio, nboot = 100, alpha = 0.05, na.rm = FALSE)

cod_met(x)

Arguments

ratio

A numeric vector of ratios centered around 1, where the numerator of the ratio is the estimated fair market value and the denominator is the actual sale price.

na.rm

Default FALSE. A boolean value indicating whether or not to remove NA values. If missing values are present but not removed the function will output NA.

nboot

Default 100. Number of iterations to use to estimate the output statistic confidence interval.

alpha

Default 0.05. Numeric value indicating the confidence interval to return. 0.05 will return the 95% confidence interval.

x

Numeric vector of sales ratio statistic(s) to check against IAAO/Quintos standards.

Functions

  • cod(): Returns a numeric vector containing the COD of ratios.

  • cod_ci(): Returns upper and lower CI as a named vector.

  • cod_met(): Returns TRUE when input COD meets IAAO standards (between 5 and 15).

See also

Other formulas: mki(), prb(), prd()

Examples

# Calculate COD
cod(ratios_sample$ratio)
#> [1] 17.81457

# Calculate COD confidence interval
cod_ci(ratios_sample$ratio)
#>     2.5%    97.5% 
#> 16.57845 19.43812