The measurement model concept was used to assess both the stochastic and bias contributions to the error structure of electrohydrodynamic (EHD) impedance spectra. The stochastic component of the error structure was determined, and a model for the error structure was identified. Regression employing weighting by the stochastic component of the error structure yielded unambiguous values for physical properties such as the Schmidt number, whereas significant ambiguity was observed using other weighting strategies. The influence of surface phenomena on the impedance response could, through use of the measurement model for assessing consistency with the Kramers-Kronig relations, be distinguished from nonstationary effects. The measurement model provided a quantitative means for assessing the utility of input signal filtering. The noise level in the measured impedance was found to be unaffected by use of input filters and, surprisingly, the time required to collect the data was increased slightly by using the filters. The estimated parameter values and their standard deviations were comparable whether or not filtering was used. The use of the measurement model to assess stochastic and bias components of the error structure extends the useful frequency range for EHD measurements and should enhance the application of EHD for assessing surface phenomena.