Right now I am a bit confused regarding the interpretation of the prior width. On the one hand I read some posts in which it is stated that the size of the prior (e.g. .2 or .7) represents “my believe” in the strength of H1 (weak believe .2, strong believe .7). Higher effect sizes are better because they are centered more far away from 0. Lower effect sizes (e.g. .2) are centered nearer to 0 and therefore the probabilities can be less well differentiated. On the other hand I read that breath of the distribution represents my uncertainty of my estimates. Therefore, a broader (width?) distribution represents more uncertainty and a more narrow distribution less uncertainty (e.g., .2 less uncertainty, .7 higher uncertainty; i.e. the other way around compared to my statement above). Can someone help me to understand these things a bit better?
Thank you very much!