Dataset Information

Running field experiments using Facebook split test.

ABSTRACT: Business researchers use experimental methods extensively due to their high internal validity. However, controlled laboratory and crowdsourcing settings often introduce issues of artificiality, data contamination, and low managerial relevance of the dependent variables. Field experiments can overcome these issues but are traditionally time- and resource-consuming. This primer presents an alternative experimental setting to conduct online field experiments in a time- and cost-effective way. It does so by introducing the Facebook A/B split test functionality, which allows for random assignment of manipulated variables embedded in ecologically-valid stimuli. We compare and contrast this method against laboratory settings and Amazon Mechanical Turk in terms of design flexibility, managerial relevance, data quality control, and sample representativeness. We then provide an empirical demonstration of how to set up, pre-test, run, and analyze FBST experiments.

SUBMITTER: Orazi DC

PROVIDER: S-EPMC7331542 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Running field experiments using Facebook split test.

Orazi Davide C DC Johnston Allen C AC

Journal of business research 20200702

Business researchers use experimental methods extensively due to their high internal validity. However, controlled laboratory and crowdsourcing settings often introduce issues of artificiality, data contamination, and low managerial relevance of the dependent variables. Field experiments can overcome these issues but are traditionally time- and resource-consuming. This primer presents an alternative experimental setting to conduct online field experiments in a time- and cost-effective way. It do ...[more]

PMID: 32834210

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Project description:BACKGROUND:Femur fractures are a common orthopedic injury in young children. Falls account for a large portion of accidental femur fractures in young children, but there is also a high prevalence of femur fractures in child abuse, with falls often provided as false histories. Objective information regarding fracture potential in short distance fall scenarios may aid in assessing whether a child's injuries are the result of abuse or an accidental fall. Knowledge of femur loading is the first step towards understanding likelihood of fracture in a fall. OBJECTIVE:Characterize femur loading during feet-first free falls using a surrogate representing a 12-month-old child. METHODS:The femur and hip joint of a surrogate representing a 12-month-old were modified to improve biofidelity and measure femur loading; 6-axis load cells were integrated into the proximal and distal femur. Femur modification was based upon CT imaging of cadaveric femurs in children 10-14 months of age. Using the modified 12-month-old surrogate, feet-first free falls from 69?cm and 119?cm heights onto padded carpet and linoleum were conducted to assess fall dynamics and determine femur loading. Femur compression, bending moment, shear and torsional moment were measured for each fall. RESULTS:Fall dynamics differed across fall heights, but did not substantially differ by impact surface type. Significant differences were found in all loading conditions across fall heights, while only compression and bending loads differed between carpet and linoleum surfaces. Maximum compression, bending, torsion and shear occurred in 119?cm falls and were 572?N, 23?N-m, 11?N-m and 281?N, respectively. CONCLUSIONS:Fall dynamics play an important role in the biomechanical assessment of falls. Fall height was found to influence both fall dynamics and femur loading, while impact surface affected only compression and bending in feet-first falls; fall dynamics did not differ across carpet and linoleum. Improved pediatric thresholds are necessary to predict likelihood of fracture, but morphologically accurate representation of the lower extremity, along with accurate characterization of loading in falls are a crucial first step.

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Running field experiments using Facebook split test.

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Running field experiments using Facebook split test.

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