Generating content at multiple levels of abstraction simultaneously is an open challenge in procedural content generation. Representing and automatically replicating the style of a human designer is another. This paper addresses both of these challenges through extending a previously devised methodology for pattern-based level generation. This method builds on an analysis of Super Mario Bros levels into three abstraction levels: micro-, meso- and macro-patterns. Micro-patterns are then used as building blocks in a search-based PCG approach that searches for macro-patterns, which are defined as combinations of meso-patterns. Results show that we can successfully generate levels that replicate the macro-patterns of selected input levels, and we argue that this constitutes an approach to automatically analysing and replicating style in level design.