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Sex‐biased dispersal is expected to generate differences in the fine‐scale genetic structure of males and females. Therefore, spatial analyses of multilocus genotypes may offer a powerful approach for detecting sex‐biased dispersal in natural populations. However, the effects of sex‐biased dispersal on fine‐scale genetic structure have not been explored. We used simulations and multilocus spatial autocorrelation analysis to investigate how sex‐biased dispersal influences fine‐scale genetic structure. We evaluated three statistical tests for detecting sex‐biased dispersal: bootstrap confidence intervals about autocorrelation r values and recently developed heterogeneity tests at the distance class and whole correlogram levels. Even modest sex bias in dispersal resulted in significantly different fine‐scale spatial autocorrelation patterns between the sexes. This was particularly evident when dispersal was strongly restricted in the less‐dispersing sex (mean distance <200 m), when differences between the sexes were readily detected over short distances. All tests had high power to detect sex‐biased dispersal with large sample sizes (n ≥ 250). However, there was variation in type I error rates among the tests, for which we offer specific recommendations. We found congruence between simulation predictions and empirical data from the agile antechinus, a species that exhibits male‐biased dispersal, confirming the power of individual‐based genetic analysis to provide insights into asymmetries in male and female dispersal. Our key recommendations for using multilocus spatial autocorrelation analyses to test for sex‐biased dispersal are: (i) maximize sample size, not locus number; (ii) concentrate sampling within the scale of positive structure; (iii) evaluate several distance class sizes; (iv) use appropriate methods when combining data from multiple populations; (v) compare the appropriate groups of individuals.