Understanding Society User Support: Issueshttps://iserredex.essex.ac.uk/support/https://iserredex.essex.ac.uk/support/support/favicon.ico?15995719382024-02-27T13:21:37ZUnderstanding Society User Support
Redmine Understanding Society User Support - Support #2060 (Resolved): Design weights taken account of in...https://iserredex.essex.ac.uk/support/issues/20602024-02-27T13:21:37ZRosie Cornish
<p>I think the answer to this is yes, but can you confirm that the household enumeration weights (e.g. a_hhdenus_xw) take account of the design weights - i.e. they are the product of the design weight and a household response weight?</p> Understanding Society User Support - Support #2031 (Feedback): Cross-Sectional Weighting Questions.https://iserredex.essex.ac.uk/support/issues/20312024-01-18T11:20:26ZIfraz Hussain
<p>Hi, I'm currently working on a cross-sectional study across waves to examine the proportion of children who live in couple-parent families where one parent reports any form of relationship distress.</p>
<p>I have three questions relating to weighting:</p>
<ul>
<li>From this analysis, I've seen changes to weighting across all previous waves and I would like to know what specifically led to the revisions?</li>
<li>Since I'm looking at participants across waves, I'm also interested in whether there is any attempt to mitigate attrition bias (e.g. changes to weighting)?</li>
<li>Given that I'm working with w_psnenui_xw weights for my study, Do you think this weighting is appropriate for examining this area of the USOC Survey data?</li>
</ul> Understanding Society User Support - Support #1890 (In Progress): Extracting PSU and Individual-L...https://iserredex.essex.ac.uk/support/issues/18902023-04-11T16:35:50ZLaurence Rowley-Abel
<p>Dear Understanding Society team,<br />I am running a multilevel model using individuals nested within census areas (LSOAs) in Waves 9, 10, 11 and 12. To account for clustering I am using the following levels in my multilevel model: individuals at the first level, PSUs at the second level and LSOAs at the third level. Therefore, from the provided weights, I need to extract separate weights for individuals and for PSUs. Having read your response here [[<a class="external" href="https://iserredex.essex.ac.uk/support/issues/1572">https://iserredex.essex.ac.uk/support/issues/1572</a>]], I am wondering if the below would be the correct approach:</p>
<p>- For the individual level, I would divide l_psnenus_xw by a_psnenus_xd (from the l_indall.dta and the a_indall.dta files respectively)<br />- For the PSU level, I would use a_psnenus_xd (from the a_indall.dta file)<br />- For the LSOA level, I would not be able to calculate a weight as it is not part of the sampling design. I would set this weight to 1 for all respondents.</p>
<p>Would this be correct? Additionally, would this mean I could only include respondents who were included at Wave 1, since I need to use the design weight (a_psnenus_xd) from Wave 1?</p>
<p>Many thanks for your help.</p>
<p>Best wishes,<br />Laurence</p> Understanding Society User Support - Support #1865 (Resolved): Changes to USOC wave data download...https://iserredex.essex.ac.uk/support/issues/18652023-02-23T16:42:31ZWilliam Shufflebottom
<p>Hi,</p>
<p>QUESTIONS</p>
<p>Q1: indscub_xw weight from wave 6 of USOC is present in our historical download of the wave 6 data but appears to be missing in the version of wave 6 we downloaded from UKData Service a few months ago and is also not listed as being in wave 6 on the USOC variable search page - can we confirm why only the indscui_xw weight is in the latest Wave 6 version, confirm it was in the original release, and if/when (and if so why) it was removed?</p>
<p>Q2: Our estimates run on the latest download of wave 1 to 12 of USOC are producing different numbers from the estimates we ran at the time of the previous wave's releases. Has there been a change to the data or weights (beyond wave 6 having a different weight) or how the weights work that could explain the difference we are seeing for all waves (bar wave 1 and wave 12) in a recent download of the data from all the waves. We are using the same weight (bar wave 6) and the same variable (sclfsat_7 in this case - but we use a range of USOC variables in our analysis).</p>
<p>BACKGROUND</p>
<p>We are producing estimates for the OECD and just discovered some differences for the estimates and CIs for the sclfsat7 variable when we re-ran historical estimates for all USOC waves 1 to 12. We run breakdowns for this variable (and others) by various domains when we update our publications and a new USOC wave has been released so we have the estimates from previous runs made at the time of USOC wave data release. We only ran the sclfsat7 variable again recently so there may be other changes.</p>
<p>We have a document for the weights to use for each variable which states that the indscub_xw weight is the correct weight to use for the sclfsat_7 variable in wave 6 but we noticed it was "missing" in the wave 6 data we downloaded around November from UK Data service (instead indscui_xw is present). As we are getting differences in our estimates and CIs for all waves (bar wave 1 and 12), this has prompted us to check with you if there have been changes made to the versions of the USOC main study wave data currently on the UK Data Service compared to what would have been available at the time each wave's data was released which could explain the differences we are seeing.</p>
<p>Your help is greatly appreciated as this has the potential to impact a lot of our publications and the current ad hoc we are working on</p> Understanding Society User Support - Support #1827 (Resolved): Correct weights to usehttps://iserredex.essex.ac.uk/support/issues/18272022-12-07T09:40:16ZAmelia Wattsamelia.watts678@outlook.com
<p>Dear Olena,</p>
<p>I have two questions regarding using weights. I’m trying to conduct a cross-sectional analysis using data from a UKHLS wave.</p>
<p>1) If I select a sub-sample using respondents interviewed in certain years/months within a wave, can I still use the existing cross-sectional weights, or will I need to make adjustments to the cross-sectional weights?</p>
<p>2) All the dependent and independent variables are from one wave (eg wave 5), apart from one independent variable which was measured at an earlier wave (eg wave 2). I will match respondents from wave 5 and wave 2 to obtain the values of this independent variable. In this case, can I still use the cross-sectional weights in wave 5, or should I use the longitudinal weights in wave 5?</p>
<p>Thank you for your help.</p> Understanding Society User Support - Support #1820 (Resolved): Cross-sectional vs longitudinal we...https://iserredex.essex.ac.uk/support/issues/18202022-11-29T08:17:45ZHenrique Neves
<p>Dear Understanding society support team,</p>
<p>Our research team is using data from the Understanding Society Main Annual Survey (waves 7 to 11) and the COVID-19 study (waves 1 to 9). In our analysis, we want to account for weights. However, we are unsure about which weighs to use.</p>
<p>Our main goal is to analyze gaps in mental health ( <em>scghq1_dv</em> ) between a Muslim and a Non-Muslim population during COVID-19. We rely on a standard difference-in-differences design, comparing the average Muslim-Non-Muslim gaps in mental health during the pandemic (Covid Survey, waves 1 to 9) with the average pre-pandemic gaps (Main Survey, waves 7 to 11). Our treatment variable takes value 1 for Covid waves and 0 otherwise. Additionally, we run an event study design, comparing Muslim-Non-Muslim gaps in mental health in each wave (Waves 8 to 11 of the Main Survey and Covid waves) relative to wave 7 of the Main Annual Survey.</p>
<p>Unfortunately, the COVID-19 study does not ask about the participants' religion. To identify Muslims in the COVID-19 dataset we extract the last religion status reported on the Understanding Society Main Survey (based on the variable <em>oprlg1</em> ) and link it with the Covid Survey through person identifiers.</p>
<p>Given our study design would you recommend we use cross-sectional or longitudinal weights?</p>
<p>Thanks in advance for your help!</p>
<p>Kind regards,<br />Henrique</p> Understanding Society User Support - Support #1779 (Resolved): Calculating persistent povertyhttps://iserredex.essex.ac.uk/support/issues/17792022-10-08T19:09:52ZFacundo Herrera
<p>Dear Team,<br />I need to estimate persistent poverty rates following the standard definition that someone is persistently poor if she/he has been poor in the current year and in two of the last three years. The first question I have is regarding attrition: if the poor were more prone to attrition, are the longitudinal weights able to account for that? And my second question is about balanced panels: if I keep only those with income data in the last 4 waves, would I be affecting the representativeness of the sample? <br />Thanks a lot for your support,</p>
<p>Facundo</p> Understanding Society User Support - Support #1777 (Resolved): Creating Longitudinal Weights for ...https://iserredex.essex.ac.uk/support/issues/17772022-10-06T16:31:47ZJoAnn Tan
<p>I have a question similar to <a class="issue tracker-3 status-3 priority-4 priority-default" title="Support: Weight for unbalanced UKHLS panel data (Resolved)" href="https://iserredex.essex.ac.uk/support/issues/1257">#1257</a>.</p>
<p>In <a class="issue tracker-3 status-3 priority-4 priority-default" title="Support: Weight for unbalanced UKHLS panel data (Resolved)" href="https://iserredex.essex.ac.uk/support/issues/1257">#1257</a>, Alita mentioned that we can create longitudinal weights for unbalanced panel. How exactly can I do that? I am quite certain that my analysis (exploring the probability of being in temporary employment) is nothing complicated and hence does not require creating my own weights. However, I really want to run a longitudinal analysis with an UNBALANCED panel. Please help, thanks! (P/S: I have read all previous posts on creating weights for unbalanced panel but I am still not sure how creating longitudinal weights for unbalanced panel could be done.)</p> Understanding Society User Support - Support #1743 (Resolved): Averaging regional data to obtain ...https://iserredex.essex.ac.uk/support/issues/17432022-08-05T10:14:30ZCarolin Schmidtcs2100@cam.ac.uk
<p>Hi there,</p>
<p>I am using wave 6 to study household heads' homeownership probabilities. I am looking at native Brits and immigrants (I came up with an immigrant dummy for every household head).</p>
<p>I would now like to generate a control variable for each of my household heads: the variable should reflect the proportion of immigrants in the UK region where the person resides (that is, every household head in e.g London will have the same immigrant share attached, etc.). I am wondering how I should calculate that average: does it have to be weighted (i.e. egen immishare = wtmean(immigrant), weight(indscui_xw) by(region) using the gwtmean package which calculates weighted statistics)? I would think so, because without weighting it, I would have an average immigrant share based on the (not-per-se representative) raw data. However, if I calculate a weighted mean, then I would effectively double-weight the data because the regression itself would be weighted too, no?</p>
<p>I am unsure how to proceed and would appreciate any help.</p>
<p>Best wishes,<br />Carolin</p> Understanding Society User Support - Support #1726 (Resolved): BHPS and Understanding Society - w...https://iserredex.essex.ac.uk/support/issues/17262022-07-13T16:58:28ZMaria Petrillo
<p>Hi,<br />I am using both the BHPS (wave 1-18) and the Understanding Society (wave 1-11) to conduct a descriptive analysis on episodes of caring over time. I would like to know what weights should I be using in this case of both a cross-section analysis and a longitudinal one. In case of a cross section analysis it seems to me that I can use xrwtuk1 for waves BH12 to BH18 and indinub_xw from wave 2 to 11. But what about all the other waves? Could you please let me know what is the best approach?</p> Understanding Society User Support - Support #1632 (Resolved): Correct weighting for mental healthhttps://iserredex.essex.ac.uk/support/issues/16322022-01-17T14:23:19ZJoe Lillis
<p>Hello all,</p>
<p>Thanks for taking the time to read my post.</p>
<p>I've recently carried out an analysis on adolescent mental health, across three waves.</p>
<p>Study design as follows: Information on 16-21 year olds at Wave 6 (n=1,748)from indresp.dta, and again, at Wave 9.</p>
<p>Covariates on previous mental health and bullying were included from waves 1, 3 and 5 (n=1,073, or 59% of original sample)of the youth survey.</p>
<p>The outcome measure was GHQ-12 scores at wave 6 and 9.Have included the pdf of the paper as is for further information.</p>
<p>My question is, what weight to use? Do USoc weights account for attrition by mental health (GHQ-12)?</p>
<p>Happy to give further detail if needed!</p>
<p>All the best,<br />Joe</p> Understanding Society User Support - Support #1622 (Resolved): Creating my own longitudinal weighthttps://iserredex.essex.ac.uk/support/issues/16222021-12-14T16:38:36ZKate Dotsikas
<p>I am running a linear regression using participants who have responded in waves 9 and 10. I understand that using the wave 10 longitudinal weight will drop individuals from my analysis who haven't responded to all of the preceding waves. From the weighting FAQ, I understand I can adjust a cross-sectional weight myself to account for the non-response in my analysis. However I'm wondering how to go about this - which cross-sectional weight do I take as a base, and from what population do I derive the weight? As I am dropping anyone not responding with a full interview in wave 9 and 10, how can I estimate the probability of non-response between these waves as everyone in my sample has responded to both? Thank you in advance for your help.</p> Understanding Society User Support - Support #848 (Closed): Clinical Depression H_COND variableshttps://iserredex.essex.ac.uk/support/issues/8482017-09-04T15:55:51ZLuca Bernardiluca.bernardi@uab.cat
<p>Dear Support group,</p>
<p>I am measuring clinical depression and I would kindly need your advice on a couple of questions. I apologise sincerely for putting immediate priority on this, but your answer might also have implications for a paper I am co-authoring within the Understanding Society EU Referendum project and we have a deadline shortly for submitting the paper.</p>
<p>As I am interested in objective depression, I was using the questions H_COND17 and H_CONDS17 to create a measure of depression. What I was doing is to assign value 1 to respondents who replied that they still have depression in H_CONDS17=Yes (as I am interested in the effects of depression, I do not care much if the person was diagnosed with depression at some point in his/her life - i.e. H_COND17=Yes - but rather it is important that the person is depressed at the time of the interview). I assign value 0 if the respondent mentioned that he/she has never been diagnosed with depression in H_COND17=No.</p>
<p>So far I was using data from waves 1, and 3 to 6 as I noticed that these two variables are available in all waves but wave 2 (<a class="external" href="https://www.understandingsociety.ac.uk/documentation/mainstage/dataset-documentation/wave/2/datafile/b_indresp">https://www.understandingsociety.ac.uk/documentation/mainstage/dataset-documentation/wave/2/datafile/b_indresp</a>), where instead a slightly different question is asked: H_CONDN17. In turn, this question is not available in all waves and sometimes is asked together with the previous two questions (e.g., <a class="external" href="https://www.understandingsociety.ac.uk/documentation/mainstage/dataset-documentation/wave/4/datafile/d_indresp">https://www.understandingsociety.ac.uk/documentation/mainstage/dataset-documentation/wave/4/datafile/d_indresp</a>).</p>
<p>My questions thus are the following. Do you please know what is the reason of such a variation and, more importantly, can I "maximise" my number of depressives by creating a measure of depression that combines both sets of questions (i.e., H_COND17 and H_CONDS17, and H_CONDN17) and makes use of all available waves (i.e. 1 to 6)?</p>
<p>My idea was to do the following:</p>
<p>gen depression = .</p>
<p>replace depression = 1 if hconds17==1 | hcondn17==1</p>
<p>replace depression = 0 if hcond17==0 | hcondn17==0</p>
<p>However, I wonder how problematic can be mixing questions that are not available in all waves, as this is certainly a point that reviewers will raise. I would really appreciate your thoughts on this.</p>
<p>Many thanks and best wishes,<br />Luca</p> Understanding Society User Support - Support #505 (Closed): Cross Sectional weights (xrwght/xrwtu...https://iserredex.essex.ac.uk/support/issues/5052016-02-17T14:02:51ZIvan Privalko
<p>Hi all,</p>
<p>I'm using the BHPS dataset (w1-w18) to look at the impact of job changes. Using the job history files, I code a variable for job changes (combining spell change "jspno" with reasons for change "jhstpy"). I'm tabulating this new variable by time to look at changes between waves, but I can't include the cross sectional weights (xrwght/xrwtuk1) in this table. After looking around for a bit I noticed that those with values in "job history files" contain no values for "cross sectional weight" variables, and those with "cross sectional weight values" have no values for "job history files" in any given year. Am I doing something wrong?</p> Understanding Society User Support - Support #55 (Closed): Do weights adjust for non-independence...https://iserredex.essex.ac.uk/support/issues/552012-05-22T09:44:11ZPeter Taylorp.j.taylor@postgrad.manchester.ac.uk
<p>I wanted to know whether the weights provided for the youth self-completion data adjust for the problem of non-independence due to different children coming from the same household. Thank you.</p>
<p>Peter Taylor</p>