Methodology: Which States' Homes Are Most at Risk of Lock Failure and Break-Ins
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This study is built entirely from public data sources, and every input can be independently retrieved and checked. We used four components per state. First, burglary rates from the FBI's Uniform Crime Reporting program, expressed as reported burglaries per one hundred thousand residents, drawn from the most recent complete reporting year available at the time of analysis. UCR figures reflect offenses reported to participating law enforcement agencies, and we note where a state's agency participation was incomplete. Second, housing age from the U.S. Census Bureau's American Community Survey, table B25035, median year structure built, on the premise that older housing stock is more likely to carry aged, worn, or ungraded door hardware. Third, renter share from ACS table B25003, tenure, since rental housing changes occupants more frequently and lock changes between tenancies are inconsistently required across states. Fourth, locksmith-licensing presence, a binary indicator of whether a state maintains locksmith licensing or registration requirements, compiled from our own verified state-by-state regulatory bundles, which cite each state's statute or licensing agency directly. No proprietary, scraped, or survey-of-convenience data was used anywhere in the index.
Each of the four components was normalized to a common zero-to-one scale across the fifty states and the District of Columbia using min-max normalization, so that the state with the highest burglary rate scores one on that component and the lowest scores zero, and likewise for each input. Median year built was inverted before normalization so that older housing stock produces a higher risk score, and licensing presence was scored so that the absence of any locksmith licensing regime contributes to higher risk, reflecting the reduced regulatory recourse available to consumers in unlicensed states. The four normalized components were then combined with equal weights into a single composite score, rescaled from zero to one hundred for readability. We deliberately chose equal weighting over any statistically fitted or judgment-based weighting scheme: fitted weights would imply a precision about the relative importance of burglary exposure versus hardware age that the underlying data cannot support. Where a component was unavailable for a jurisdiction, we did not reweight the remaining components to fill the hole. The gap is stated in the published table, the affected composite is flagged as computed on partial data, and readers can see exactly which inputs each state's score rests on.
This index is a descriptive ranking tool, not a predictive model, and several limitations bound what it can claim. FBI UCR burglary figures count offenses reported to police, so states differ in reporting practices, agency participation, and the share of incidents that ever reach a report; the transition among agencies to the NIBRS reporting system has also affected year-over-year comparability. Burglary rates describe reported property crime generally and are not a direct measure of lock failure, for which no public dataset exists. Median year built is a coarse proxy for hardware condition: an old house may have new certified locks, and a new house may have ungraded builder hardware. Renter share captures turnover exposure, not the actual rekeying practices of any landlord. Licensing presence is binary and does not grade the stringency of a state's regime. ACS estimates carry published margins of error, which are wider for smaller states. Finally, equal weighting is itself an editorial choice, made for transparency rather than derived from evidence about relative effect sizes. State-level scores should not be read as statements about any individual home, neighborhood, or city, and small differences in composite scores between adjacent ranks are not meaningful.
All burglary figures should be attributed to the FBI Uniform Crime Reporting program; housing age and tenure figures to the U.S. Census Bureau's American Community Survey, tables B25035 and B25003; and licensing determinations to the statutes and agencies cited in our state regulatory bundles, which are published alongside this study. When citing the composite index itself, please attribute it to LocksmithCallNow.com and link to this methodology page so readers can evaluate the construction and its limits for themselves. We treat this as a living document: if a state agency, researcher, or reader identifies an error in an input value or a licensing classification, we will correct the dataset and note the change here. Journalists and researchers are invited to request the full state-level CSV, including every raw input, each normalized component, the flags for partial-data composites, and source citations per field, by contacting our editorial team, and we will provide it at no cost with no conditions beyond accurate attribution.