Understanding Society User Support: Issueshttps://iserredex.essex.ac.uk/support/https://iserredex.essex.ac.uk/support/support/favicon.ico?15995719382022-03-29T10:29:15ZUnderstanding Society User Support
Redmine Understanding Society User Support - Support #1673 (In Progress): pensioner_dv seems to be wrong ...https://iserredex.essex.ac.uk/support/issues/16732022-03-29T10:29:15ZTom Waters
<p>Hi,</p>
<p>The pensioner_dv variable is supposed to determine whether the respondent is past State Pension Age (SPA). But for men, in wave K, all men aged 64 or younger are defined as not being past SPA, and all men aged 65 or older are. However, men born after 6 December 1953 have a SPA after their 65th birthday (<a class="external" href="https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/310231/spa-timetable.pdf">https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/310231/spa-timetable.pdf</a>)</p>
<p>For women this does not seem to be a problem - at least, there are 65 year old women in wave K for whom the pensioner_dv variable says they are below SPA.</p>
<p>(Though, there are 36 women in wave K who are 60 years old and pensioner_dv indicates that they are past SPA. Presumably that can't be right?)</p> Understanding Society User Support - Support #1653 (Resolved): Representativeness of lone mothershttps://iserredex.essex.ac.uk/support/issues/16532022-02-07T10:28:37ZTom Waters
<p>Hi,</p>
<p>I have been comparing the UKHLS data to data from the FRS and LFS. For reasons not clear to me, the UKHLS data seem to be very significantly different when looking at lone mothers.</p>
<p>I attach two .do files which calculate the share of lone mothers that are homeowners, and the age that lone mothers finished education, in both the FRS and UKHLS (for 2009-10 data in FRS, and wave A in UKHLS). It should run if you simply change the "path" global at the top to specify where FRS/UKHLS data are saved.</p>
<p>The results are very different. In the FRS, 16% of lone mothers finished full time education aged 19 or older, and 35% own their own home. In UKHLS those figures are 32% and 47% respectively.</p>
I have tried a number of variations:
<ul>
<li>These differences hold in other years/waves too</li>
<li>The differences persist if you do not weight the data</li>
<li>The LFS gives figures very similar to FRS, not UKHLS</li>
<li>If you look at the whole population (rather than just lone mothers), the two surveys are pretty similar for homeownership, but there is still a much higher rate of leaving education at 19 or later in UKHLS</li>
<li>Similar differences seem to hold for lone mothers for other outcomes, including employment (higher in UKHLS) and the take-up of out-of-work benefits (lower in UKHLS)</li>
</ul>
<p>Very grateful for any guidance in what might be going on here.</p> Understanding Society User Support - Support #1265 (Resolved): Variable storage types changing fr...https://iserredex.essex.ac.uk/support/issues/12652019-10-24T11:59:03ZTom Waters
<p>Hi,</p>
<p>I wanted ask whether it would be possible to ensure that data storage types for a given variable not change from wave to wave. For example, in the Special Licence Stata data I am using, w_jshrs changes from type 'int' in wave E, to 'float' in wave F, to 'byte' in wave G. While this doesn't matter for most analysis (e.g. Stata analysis), it does matter if you are trying to read the data into a programme that is more specific on data types. If it is not possible to keep them consistent, it would be very useful to have a list which details every variable which changes type over the survey. Apologies if that is already available and I can't find it.</p>
<p>(I downloaded the data I am using December 2018, which may not be the very latest version)</p>
<p>Many thanks,<br />Tom</p> Understanding Society User Support - Support #1221 (Resolved): Using UKHLS at the quarterly levelhttps://iserredex.essex.ac.uk/support/issues/12212019-07-31T10:33:03ZTom Waters
<p>Hi,</p>
<p>I am trying to look at various outcomes by quarter in a dataset which pools multiple UKHLS waves together with another dataset (the FRS).</p>
<p>However I understand that there is non-random sampling within wave. For example, in wave C Northern Ireland is only sampled in the first year (2011). I was sent a document from someone at Essex which discusses pooling data from different waves in UKHLS. It says, "The weights provided currently are not designed for pooling as they are scaled to a mean value of 1.0 within each wave, and therefore produce different weighted sample sizes in each wave. As a result, cases from later waves will be under-represented."</p>
<p>I have three questions:<br />1. Why is it that later waves would be under-represented? I should've thought that if they had the same average weight, then cases would be equally represented when you weight?<br />2. What steps should I take to ensure that quarterly level outcomes are representative?<br />3. Are there any additional steps I should take to take account of the fact that we are pooling with the FRS? Currently we are making sure that, within a financial year, the FRS observations and UKHLS observations have the same average weight. Is that sufficient?</p>
<p>Many thanks for your help.</p>
<p>Tom</p> Understanding Society User Support - Support #921 (Resolved): Council tax variablehttps://iserredex.essex.ac.uk/support/issues/9212018-02-15T17:04:15ZTom Waters
<p>Hi,</p>
<p>I have the special licence data for USoc and harmonised BHPS. I was sure that before there was a variable called dep9ctax which had the council tax bill of the household in at least the harmonised BHPS, but it doesn't seem to be there anymore. Am I just missing it or has it been removed from the special licence version?</p>
<p>Thanks<br />Tom</p> Understanding Society User Support - Support #916 (Resolved): Two questions about weightshttps://iserredex.essex.ac.uk/support/issues/9162018-02-12T09:03:03ZTom Waters
<p>Hi,</p>
<p>I have two questions about weights that perhaps you can help me with.</p>
<p>First, the documentation states that the right weight depends on the 'lowest' questionnaire that you are using. e.g. if you are using information from the adult interview and adult & proxy interview, you should use the adult interview weights. Can you explain to me why these weights vary, or point me to a source which could explain? I am basically wondering what to do if we want to include some questions not on the proxy questionnaire, but I am happy to make some assumptions for proxies.</p>
<p>Second, in the harmonised BHPS there seems to be one (set of) weights if we want to include proxies and non-respondents - lewght - and one if we want to just include those that give a full interview - lrwght. What should I do if we want to perform analysis on full respondents and proxies, but not non-respondents?</p>
<p>Grateful for any help.</p>
<p>Thanks,<br />Tom</p>