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The variance of the model explained by each random effect f..:

James Parmley (12024621) ; Ben Jones (554472) ; Tom Sawczuk (12024624).
https://figshare.com/articles/dataset/The_variance_of_the_model_explained_by_each_random_effect_for_all_weekly_training_load_metrics_/19098270. , 2022

Link: https://doi.org/10.1371/journal.pone.0263093.t003

RT Journal
T1 <Title>The variance of the model explained by each random effect for all weekly training load metrics</Title>

UL https://suche.suub.uni-bremen.de/peid=base-ftsmithonian:oai:figshare.com:article_19098270&Exemplar=1&LAN=DE
				
A1 James Parmley (12024621)
A1 Ben Jones (554472)
A1 Tom Sawczuk (12024624)
A1 Dan Weaving (6335525)
YR 2022
K1 Evolutionary Biology
K1 Sociology
K1 Science Policy
K1 Environmental Sciences not elsewhere classified
K1 Biological Sciences not elsewhere classified
K1 season study quantifying
K1 repeated measures design
K1 distance (> 7
K1 also expressed relative
K1 training load varies
K1 training load variable
K1 external training load
K1 microcycle variability ranged
K1 microcycle lengths exist
K1 match microcycle lengths
K1 study investigated differences
K1 one separate microcycles
K1 div >< p
K1 5 – 7
K1 training load
K1 microcycle lengths
K1 session duration
K1 likely due
K1 largest magnitude
K1 head coaches
K1 greatest number
K1 comparing 5
JF https://figshare.com/articles/dataset/The_variance_of_the_model_explained_by_each_random_effect_for_all_weekly_training_load_metrics_/19098270
LK http://dx.doi.org/https://doi.org/10.1371/journal.pone.0263093.t003
DO https://doi.org/10.1371/journal.pone.0263093.t003
SF ELIB - SuUB Bremen

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