city200

<p>A data.frame of one decision-maker with weights the same as Saaty2004;textualahpsurvey, with the pairwise comparisons of <code>atts</code>: <code>c('cult', 'fam', 'house', 'jobs', 'trans')</code>, about a choosing the best city to live in based on five attributes: Culture, Family, House, Jobs, and Transportation. The choices of 200 decision-makers are simulated based on the underlying weights and randomness generated by a normal random distribution. The true weights are stored in <code>data(city1)</code>. The normal random distribution was set with a mean at the true weight value and a standard deviation of <code>2,1,2,1.5,2,1.5,2.5,0.5,0.5,1</code> in chronological order of the columns in <code>city200</code>.</p>

datasets

The Analytic Hierarchy Process is a versatile multi-criteria decision-making tool introduced by Saaty (1987) <doi:10.1016/0270-0255(87)90473-8> that allows decision-makers to weigh attributes and evaluate alternatives presented to them.    This package provides a consistent methodology for researchers to reformat data and run analytic hierarchy process in R on data that are formatted using the survey data entry mode. It is optimized for performing the analytic hierarchy process with many decision-makers, and provides tools and options for researchers to aggregate individual preferences and test multiple options. It also allows researchers to quantify, visualize and correct for inconsistency in the decision-maker's comparisons.

Frankie Cho

ahpsurvey

Analytic Hierarchy Process for Survey Data

city200 function

<p>A <code>data.frame</code> with 200 row and 10 variables, which are pairwise comparisons of <code>atts</code>.</p>

city200: A dataframe of 200 simulated decision-makers based on Saaty2004;textualahpsurvey

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