1986
DOI: 10.2307/1938526
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The Importance of Statistical Power When Testing for Independence in Animal Movements

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Cited by 59 publications
(17 citation statements)
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“…This type of analysis is usually used to determine at what temporal scale data are sufficiently independent to be used as independent observations (Swihart & Slade, 1985; Underwood, 1997). The data used to construct these relationships were assumed to be independent after the autocorrelogram analysis showed no statistically significant temporal autocorrelation for all the possible time lags (Swihart & Slade, 1985, 1986). Considering the short‐term nature of these experiments in comparison with the whole summer season and the outcome of partial autocorrelogram analysis, we concluded that the time factor would have only a mild effect on the estimation of the regression parameters despite the lack of genuine replication.…”
Section: Discussionsupporting
confidence: 92%
“…This type of analysis is usually used to determine at what temporal scale data are sufficiently independent to be used as independent observations (Swihart & Slade, 1985; Underwood, 1997). The data used to construct these relationships were assumed to be independent after the autocorrelogram analysis showed no statistically significant temporal autocorrelation for all the possible time lags (Swihart & Slade, 1985, 1986). Considering the short‐term nature of these experiments in comparison with the whole summer season and the outcome of partial autocorrelogram analysis, we concluded that the time factor would have only a mild effect on the estimation of the regression parameters despite the lack of genuine replication.…”
Section: Discussionsupporting
confidence: 92%
“…Secondly, we side‐stepped the problem of temporal autocorrelation in the data (Swihart & Slade 1985, 1986; Solow 1989; Cresswell & Smith 1992; Rooney, Wolfe & Hayden 1998; Salvatori et al . 1999) by using the individual as the sampling unit for estimating usage.…”
Section: Discussionmentioning
confidence: 99%
“…This assumption relied on the central limit theorem and therefore required that sampling units were independent. By using the individual, rather than the trip or the satellite location, as our sampling unit, we guaranteed that variability in spatial usage would not be underestimated as a result of serial autocorrelation (Swihart & Slade 1985, 1986; Hansteen, Andreassen & Ims 1997). We followed the advice of Otis & White (1999) that ‘if the objective of the study is to make inferences about the population of animals from a representative sample of radio‐tagged individuals then the appropriate sampling or experimental unit is the individual, not the single location’.…”
Section: Methodsmentioning
confidence: 99%
“…Se realizó una prueba de independencia de los datos (ArcMAp versión 9.2, y la extensión "Hawths Tools"), para verificar si el intervalo escogido para la toma de datos fue el adecuado (Swihart & Slade 1985, 1986Rodgers et al 2005).…”
Section: Materiales Y Métodosunclassified