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It’s been a while since a little burst of statistical fun hit the blogosphere but summer is sort of here, and you may be faced with a choice of tracks\u00a0in a forest and unsure which one to take …<\/p>\nIt’s been a while since a little burst of statistical fun hit the blogosphere but summer is sort of here, and you may be faced with a choice of tracks\u00a0in a forest and unsure which one to take …<\/p>\n
Path analysis will not aid you.<\/p>\n
Path analysis (aka ‘structural equation modelling’ … sort of …) is a type of regression analysis, where you try to predict one thing that you don’t know (for example, final hight of a child) using stuff you do know (like the height of the parents, current age, height & pubertal status).\u00a0<\/p>\n
‘Normal’ regression analysis says “how are these things weighted?”<\/p>\n
‘Path’ style analysis sets up a hypothesis (final height depends on current age & height, but the power of these differ depending on puberty phase, and they are initially determined by parental height too) and then sees how strong those connections are.<\/p>\n
What usually happens is you show that they aren’t very strong. (‘Cause the *real* path involves knowing the bone age, current IGF1 levels, nutritional status and duration of sleep nightly* and the path model works by assuming you know All The Things.) But they might help you understand suggested causality a little bit more.<\/p>\n
* everyone knows that you only grow in your sleep and that is why children sleep so much ’cause they need to grow<\/p>\n","protected":false},"excerpt":{"rendered":"
It’s been a while since a little burst of statistical fun hit the blogosphere but summer is sort of here, and you may be faced with a choice of tracks\u00a0in a forest and unsure which one to take … Path analysis will not aid you. Path analysis (aka ‘structural equation modelling’ … sort of …) […]<\/p>\n