This paper describes a novel methodology for the detection of speech patterns. Lagged co-occurrence analysis (LCA) utilizes the likelihood that a target word will be uttered in a certain position after a trigger word. Using this methodology, it is possible to uncover a statistically significant repetitive temporal patterns of word use, compared to a random choice of words. To demonstrate this new tool on autobiographical narratives, 200 subjects related each a 5-min story, and these stories were transcribed and subjected to LCA, using software written by the author. This study focuses on establishing the usefulness of LCA in psychological research by examining its associations with gender. The application of LCA to the corpus of personal narratives revealed significant differences in the temporal patterns of using the word "I" between male and female speakers. This finding is particularly demonstrative of the potential for studying speech temporal patterns using LCA, as men and women tend to utter the pronoun "I" in comparable frequencies. Specifically, LCA of the personal narratives showed that, on average, men tended to have shorter interval between their use of the pronoun, while women speak longer between two subsequent utterances of the pronoun. The results of this study are discussed in light of psycholinguistic factors governing male and female speech communities.