Understanding Society User Support: Issueshttps://iserredex.essex.ac.uk/support/https://iserredex.essex.ac.uk/support/support/favicon.ico?15995719382022-06-13T11:06:10ZUnderstanding Society User Support
Redmine Understanding Society User Support - Support #1715 (Resolved): Longitudinal Weighting of Non-Move...https://iserredex.essex.ac.uk/support/issues/17152022-06-13T11:06:10ZSue Easton
<p>Hi, I have searched and can't find these key words in any posts.</p>
<p>Due to limitations of time I need to limit my analysis to individuals who have not changed location since they entered the survey in Wave 1 (UKHLS sample and any others in from Wave 1 with more than 1 wave).</p>
<p>This means some people's data will be right censored due to household moves.</p>
<p>How will this affect weighting?</p>
<p>Will I need to calculate new weights? As variables such as age are highly likely to be correlated with the "risk" of moving home.</p>
<p>Thanks.</p>
<p>Sue EAston</p> Understanding Society User Support - Support #1705 (Resolved): Longitudinal Weighting of UKHLS Da...https://iserredex.essex.ac.uk/support/issues/17052022-05-24T13:02:37ZSue Easton
<p>Hi,</p>
<p>1. Are there any reference documents on how/where to enter the UKHLS variables: PSU, strata and k_indinus_lw in order to weight the survey data for multilevel modelling in MLwiN please?</p>
<p>A link to a simple "how to" guide with examples would be really useful if possible please (due to limitations of time). Thanks.</p>
<p>Also: <br />2. If the longitudinal weight k_indinus_lw excludes GPS individuals who have missed waves over time in the series a-k (1-11), is there any point trying to "backfill"/impute data for their missed waves?</p>
<p>Thanks!</p>
<p>Sue Easton</p> Understanding Society User Support - Support #1645 (Resolved): How to Deal with Missingness in He...https://iserredex.essex.ac.uk/support/issues/16452022-01-31T15:50:45ZSue Easton
<p>Hi,</p>
<p>How to Deal with Missingness in Health Variables Over Time</p>
<p>I'm looking t health variables in UKHLS waves 1-11, and may individuals have incomplete data across the full timespan.</p>
<p>I'm wondering whether "missingness" across time/waves in UKHLS is generally considered MCAR/MAR/NMAR, as in this case it may indeed be linked to episodes of illness, and how other researchers have dealt with the issue of missing data?</p>
<p>I am dubious about imputing values using multiple imputation when the values I would use to impute are the same ones I will be entering into a multilevel analysis of health outcome.</p>
<p>Any advice or references on how to deal the missingness across time/waves gratefully received!</p>
<p>Thanks,</p>
<p>Sue E.</p> Understanding Society User Support - Support #1642 (Resolved): Incomplete Merge of Longitudinal i...https://iserredex.essex.ac.uk/support/issues/16422022-01-28T12:20:52ZSue Easton
<p>Hi,</p>
<p>I have merged (appended) core individual variables from all UKHLS indresp waves a - k (1 - 11) longitudinally, and all waves of core household vars from hhresp longitudinally. Both files have data from all 11 waves.</p>
<p>But when I merge these longitudinal indresp with hhresp datasets many to one (m:1) on hidp, there is unmatched data from both the indresp and hhresp datasets, which I wasn't really expecting. (My code is good, I've done this before).</p>
<p>Can someone explain why this might be so that I understand what's going on with the data before I continue my analysis please? I.e. are there people who have answered the household questions (such as proxy respondents), but who have not completed the individual questionnaires?</p>
<p>Also if this is documented somewhere please can you direct me to where I can find the answers to this sort of question.</p>
<p>Many thanks for your help! Much appreciated!</p>