Integral membrane proteins are the primary targets of novel drugs but are largely without solved structures. As a consequence, hydrophobic moment plot methodology is often used to identify putative transmembrane alpha-helices of integral membrane proteins, based on their local maximum mean hydrophobic moment (<microH>) and the corresponding mean hydrophobicity (<H>). To calculate these properties, the methodology identifies an optimal eleven residue window (L = 11), assuming an amino acid angular frequency, theta, fixed at 100 degrees. Using a data set of 403 transmembrane alpha-helix forming sequences, the relationship between <microH> and <H>, and the effect of varying of L and / or theta on this relationship, was investigated. Confidence intervals for correlations between <microH> and <H> are established. It is shown, using bootstrapping procedures that the strongest statistically significant correlations exist for small windows where 7 < or = L < or = 16. Monte Carlo analysis suggests that this correlation is dependent upon amino acid residue primary structure, implying biological function and indicating that smaller values of L give better characterisation of transmembrane sequences using <microH>. However, varying window size can also lead to different regions within a given sequence being identified as the optimal window for structure / function predictions. Furthermore, it is shown that optimal periodicity varies with window size; the optimum, based on <microH> over the range of window sizes, (7 < or = L < o= 16), was at theta = 102 degrees for the transmembrane alpha-helix data set.