city1

<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. Negative values in the data denote that the attribute on the left is more important than the right, thus if used with <code>ahp.mat</code>, <code>negconvert</code> must be set to <code>TRUE</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

city1 function

<p>A data frame with 1 row and 10 variables, which are pairwise comparisons of <code>atts</code>.</p>

city1: Dataframe of one decision-maker based on Saaty2004;textualahpsurvey

Description

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