How preconceived ideas of sample size nearly soured a great project
Pharma Specific Conjoint offered an ideal solution for our client. However, the significantly smaller sample size, compared to that of discrete-choice conjoint, lead to the project being met with reservations. A solution was needed to demonstrate the accuracy of our methodology.
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The asset in dermatology looked promising
Our client’s dermatology asset was in late phase trials and initial data read-outs looked promising. Internal expectations were high, although there was still uncertainty around the asset’s profile.
Inpharmation’s experience in dermatology, along with our Pharma-Specific Conjoint™ platform, offered the ideal solution to inform the asset’s market-share potential.
However, a new project lead had reservations
After the project had been commissioned, a new project lead joined the client’s team. The lead had experience with discrete-choice conjoint and was skeptical of our approach because of the significantly smaller sample size.
This was understandable because the lead had only used discrete-choice conjoint in the past, and, with discrete-choice conjoint, much larger sample sizes are needed. There is lots of research supporting this:
- “Only when the random sample size is 500 or greater do the estimates start to cluster around the true parameters.”
Behavioral Research Group
It was too late to change course as the project had already been commissioned and internal deadlines had to be met. It would have been too time consuming to change approach.
A solution was needed to prove the accuracy of Pharma-Specific Conjoint…