Encyclopedia of Biostatistics 2005
DOI: 10.1002/0470011815.b2a15150
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Spearman Rank Correlation

Abstract: In a nonparametric (distribution‐free) approach to the correlation between two sets of measurements made on the same individuals, each set may be ranked in order of magnitude. The standard (Pearson) product‐moment correlation coefficient is calculated on the two sets of ranks. Simple formulae are available, and adjustments are made for tied ranks. Test and estimation procedures are described. The relationship with the Kendall rank correlation coefficient is discussed.

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Cited by 308 publications
(152 citation statements)
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“…The coefficient ρs (Rho) of Spearman was applied because it is a robust and efficient estimator in case of ranks (Croux & Dehon, 2010;Zar, J. H., 2005), and it is one of the coefficients most commonly used to measure the association between two ranks of attributes (qualitative variables) and to know the direction of the association (Masson et al, 2003;Matthys et al, 2004). The measure and the direction of the association between ranks of attributes of couples of small fruits may provide information about similarities between fruits or dissimilarities, according to consumers, and therefore provide information about similarities of preferences for small fruits.…”
Section: Statistical Data Analysismentioning
confidence: 99%
See 1 more Smart Citation
“…The coefficient ρs (Rho) of Spearman was applied because it is a robust and efficient estimator in case of ranks (Croux & Dehon, 2010;Zar, J. H., 2005), and it is one of the coefficients most commonly used to measure the association between two ranks of attributes (qualitative variables) and to know the direction of the association (Masson et al, 2003;Matthys et al, 2004). The measure and the direction of the association between ranks of attributes of couples of small fruits may provide information about similarities between fruits or dissimilarities, according to consumers, and therefore provide information about similarities of preferences for small fruits.…”
Section: Statistical Data Analysismentioning
confidence: 99%
“…The correlation of ranks introduced by Spearman is one of the oldest and best known of nonparametric procedures for studying ranks of preferences (in qualitative studies). The rank correlation coefficient, ρs (Rho), is generally expressed as ρs = 1 − 6 (Σ d2 ⁄ (n3 − n)), where n is the number of measurements in each of the two variates in the correlation, Σd2 = Σni=1 d2i, and di is the ranked difference between the ith measurements for the two variates (Zar, J. H., 2005).…”
Section: Statistical Data Analysismentioning
confidence: 99%
“…As the number of barriers differed between participant groups, it was felt inappropriate to compare proportions with individual barriers. Comparisons between participant groups were therefore made by comparing ranking using weighted rank correlation with the top-down correlation coefficient shown (r T ), based on Savage scores (13). The closer the r T is to 1.0, the greater the concordance between groups.…”
Section: Statisticsmentioning
confidence: 99%
“…Spearman rank correlation is a non-parametric measure of the monotomic association between two numeric variables (Zar, 1998). The idea of the Spearman Rank used here will check if it is the case that on the global export market, either country is competing for share or is just complementary in the export of that product or there is no relationship at all between the two countries.…”
Section: Spearman Rank (R S ) Correlation Coefficientmentioning
confidence: 99%
“…The magnitude of the sum is related to the significance of the correlation. The advantage of the Spearman Rank coefficient is that it is a nonparametric technique thus it is not impacted by the population distribution (Zar, 1998).…”
Section: Business and Economic Researchmentioning
confidence: 99%