Cyber Citizens for Justice, Inc. [CCFJ] surveyed owners of residences in deed-restricted communities in Florida in August Ė October of 2012.  The survey elicited respondentsí views about ten [10] possible legislative reforms for Home Owners Associations.  450 usable responses were received and analyzed.  Responses which were anonymous or failed to provide an answer to any of the 10 key questions were rejected.  Duplicate responses also were rejected.  CCFJís secretary, Dr. David Goldenberg, entered the data into a standard database, then analyzed it and produced this report.


Numbers in brackets [#] in the reportís tables refer readers to a set of footnotes at the end of this report. Some basic statistical tools were used to analyze the data in order to extract as much information as possible for decision making.  Those techniques also are explained in the footnotes.


Summary Table 1 shows that all ten [10] reforms are very highly desired.  The lowest rating of YES votes was 84.7% in favor of paying a $4 annual fee for an effective HOA regulatory agency.   The highest value was 95.4% in favor of better rules for turning over or ending developer control of HOAs to allow residents to determine their own governance practices.  Another test revealed that the order of asking the 10 key questions did not influence the size of the pro and con ratings for those issues. 


In the survey at hand thereís less than one chance in a million that Florida residents in deed-restricted communities actually are neutral on any of the ten issues according to the t-tests. A huge majority of residents in deed-restricted communities in Florida clearly desire every one of the proposed reforms.  Conversely, these results definitely are not the whim of a vocal minority. Samples are drawn from populations and data from the sample are used to estimate the views of the population as a whole.  Statistical analyses enable one to estimate the odds that the population from which a sample was drawn really differs from the sample values or, in other words, that the sample misrepresents the nature of the population. (See KEY FINDINGS FROM TABLE 1)


Seven [7] traits of respondents and seven [7] traits of their communities were used to enhance understanding of the analytic results.  The respondent traits were:  


are or arenít an attorney,  
2. are or arenít a community association manager [C.A.M.],  
3. are a woman or a man,  
4. are or arenít a CCFJ member,  
5. are full-time or part-time resident,  

have or havenít served or are or are not presently serving on an associationís board of directors,

7. did or did not make a comment.

See Table 2-A for details. (See KEY FINDINGS FROM TABLE 2-A)


Statistical analysis indicated that residents who had served or were serving on a communityís board of directors held notably different views from those respondents who had not done so.

The seven [7] community traits considered were:  


type of community [HOA vs. CONDO], 


region of the state where the community is located [north, central, west coast, east coast and south],  


size of the community [small, that is less than 500 lots, vs. large, that is at least 500 lots],


developer does or doesnít control the board,


a CAM is or isnít used,  


there is or isnít a 55+ age restriction, and  


pets are or arenít allowed.  Statistical analysis indicated that very subtrait was notably different and important in practice.  

See Table 2-B for details. (See KEY FINDINGS FROM TABLE 2-B)


Summary Table 3 sorts and summarizes the 164 comments made.  



Tables 4-A and 4-B contrast and analyze the comments by community traits, and respondent traits, respectively.  (See Key Findings from TABLE 4-A and TABLE 4-B)


Given ten [10] issues and 14 traits, 140 cross-tabulations might be amenable to analysis via Chi-squared test.  A Chi-squared test would indicate whether or not a given trait influenced the answer to a particular key question.  For example, do small and large communities have meaningful different views about the desirability of a proposed change in the law?


Only four [4] or 2.9% of the ratings of the issues almost certainly were influenced by a trait of their communities.  Moreover, those four issues were in the top five of most desired reforms.  Where a respondent trait, board service or non-service, influenced the votes for or against three different issues, namely, turnover of control, a regulatory agency and bank liability. Two traits, region where a community was located and whether or not the community employed a CAM, influenced the votes for or against reforming the eligibility rules for board service.


These results imply that it would be quite misleading to draw any conclusion(s) about the population of residents in Florida deed-restricted communities just from a given region or using a CAM or those with past/present board service since only two community traits [region and use of a CAM] and one trait of respondents [past/present board service] sometimes matter.  Conversely, the size of a community, its type [HOA vs. Condo], control by a developer, 55+ restriction, or allowing pets didnít impact the votes on the issues of interest.  Nor did the other respondent traits matter, that is ó full-time vs. part-time residency, gender, CCFJ membership, being an attorney or being a CAM or making a comment.  [Note well: the community trait of employing a CAM is not the same as the respondent trait of being a CAM.]


34 or 24.3% of the 140 possible cross-tabulations had too small a value in a cell, that is ó less than 5, to calculate a reliable Chi-Square value to use in testing for the presence or absence of a relationship.


The Chi-Square tests of the 102 or 72.9% of remaining cross-tabulations found no credible relationship between an issue and a trait.