May 22 2013

Lift while you climb

At the recent AAPOR conference in Chicago, I attended a session on women leaders in the association. I hate to be conscious of it but I frequently find myself noticing just how few women are conference speakers in comparison to men.
I was hoping to hear insights from these women on how they managed to be strong and opinionated without being perceived as bitches and bossy-pants. That in particular is a gender bias I don’t understand but they didn’t really answer that question.
More importantly, this session made me think that that isn’t the issue. The issue really is lifting. Man or woman, sighted or blind, old or young, walking or wheeling, are you personally lifting as you climb?
I thought back to myself. I don’t see myself as a climber but rather someone who surprisingly lands in places that make me happy. But outsiders might see it as climbing. So as i’ve climbed, have I lifted?
I have co-authored papers with junior staff. (Some of whom have recoiled and refused but I think trying counts.) I have poked and prodded into the personal lives of others to figure out how I can push them closer to where they want to go. (Some have let me and I helped push them out of my company and into grad school.)
But I haven’t lifted enough. Beware colleagues and friends…

Written on the go

May 21 2013

10 answers to contemporary market research questions #MRX

Are you fresh out of school? Full of book knowledge but short on practical knowledge? Then this book is for you!

Join the book launch on May 22nd here!

10 Answers to Contemporary Market Research Questions provides new entrants to market research with a first point of reference in a fast changing industry. In  market research, there are some key concepts, ideas, and pieces of knowledge that even the newest researcher (or a researcher new to a topic) should have at their fingertips.

The 10 Answers to Contemporary Market Research Questions aims to present those key items as a set of questions and answers. While its not a manual of how to conduct research, it does provide nuggets of information that will enable new (and sometimes older) researchers to orientate themselves, and avoid walking into too many of the traps that the changing world of market research can create.market research, there are some key concepts, ideas, and pieces of knowledge that even the newest researcher (or a researcher new to a topic) should have at their fingertips.

The Project Team
The book has been created through the voluntary and collaborative efforts of a team of people brought together by ESOMAR to generate this resource as part of the celebration of its 65th year. The project curators are Finn Raben, director general of esomar, Sue York, chief curator of Newmr, and Ray Poynter, Director of Vision Critical University, Vision Critical.

The contributing authors are:
Suz Allen, Sven Arn, Reg Baker, Susan Bell, Pete Cape, Alison Dexter, Dirk Huisman, Nasir Khan, Kathryn Korostoff, Phyllis Macfarlane, Omar Mahmoud, Bernie Malinoff, Katie O’Connor, Stephen Paton, Annie Pettit, Pravin Shekar, Anouk Willems and Tom Wilms.

The editors are Ray Poynter and Sue York.

Join the book launch on May 22nd here!

Related articles
May 17 2013

Public Opinion and the Environment #AAPOR #MRX

AAPOR… Live blogging from beautiful Boston, any errors are my own…

Public Opinion and the Environment; Moderator: Robert Eisinger, Savannah College of Art and Design

The Weathering of Skepticism: An Examination of American Views on the Existence of Climate Change
Christopher P. Borick, Muhlenberg College Institute of Public Opinion, Barry G. Rabe, University of Michigan

  • 2008, the majority of americans believe in global warming
  • 2010:  dropped off the agenda in DC, percentage believing in global warming is declining, people wonder if it’s a hoax
  • 2013: rate has risen but not back to previous levels, obama addressed it in two important speeches
  • Shifts in views related to level of attention by congress and president
  • Is there evidence of global warming? went from 72,65,52,58,55,62,65,68,67,62 from 2008 to 2013 (couple measurements per year)
  • Most significant factor in belief of global warming is partisanship. [wow, ridiculous!]
  • Why believe? Glaciers melting, warmer temperatures, weather change, scientific research. Personal experience is the top reason.
  • Drought was important in believing global warming, but more so for people in the southeast
  • Increasingly people think climate change is not occuring due to religious factors

Global Warming Attitudes Among Local News Viewers and Non-Viewers; Media Market Comparative Analysis and Change Over Time; Amy Simon, Goodwin Simon Strategic Research, Leora Lawton, Tech Society Research; UC Berkeley, Berkeley, Population Center, Adam D. Probolsky, Probolsky Research LLC, Paul A. Hanle, Climate Central

  • More people think global warming is happening 61% last year, 67% this year
  • People who watch the weather on tv are more likely to think global warming is happening
  • If you explain to people what global warming is, then the rate increases 5%
  • People think the earth is getting warmer due to 1) humans 2) earth patterns 3) both
  • People assume the global warming term refers more to human intervention
  • only 50% think it’s a serious problem
  • 79% of people think they are well informed [wow. people really overestimate their knowledge]
  • answers to factual questions vary due to ideology

Polls, Publics and Pipelines: Mapping Public Opinion Toward the Keystone XL Pipeline in the United States and the Northern Gateway Pipeline in Canada; Timothy B. Gravelle, PriceMetrix Inc.

  • Canada and US do have different cultural values even though we look alike
  • How do canadians and americans differ in their opinions of the oil pipelines
  • Proximity and distance likely matter – NIMBY
  • Most predictive variables in model were liberal ideology, attitudes towards economy
  • People who think the economy is poor were more in favour
  • Support increases for people who are closer to the pipeline – approval is high regardless of opinion about economy

Emphasis Framing and Americans’ Perception of Scientific Consensus: Scientists Agree on “Climate Change” but not on “Global Warming”; Jonathon P. Schuldt, Cornell University, Sungjong Roh, Cornell University
Norbert Schwarz, University of Michigan

  • 26% of people say they see no evidence of global warming; 51% of convervatives vs 7% of democrats, reliable divide for over a decade
  • are there differences if you talk about global warming versus climate change?
  • often used interchangeably
  • could using the different words create different findings? [well, that's an obvious yes]
  • Aggregate sample – 68% say yes to global warming, 74% say yes to climate change
  • Republicans more likely to be affected by the word change
  • Reduce the partisan divide if you say climate change
  • Democrats don’t care which word. Replicans more likely to believe in climate change, not global warming.
Related articles
May 17 2013

#AAPOR Presidential Address: The total error approach by Paul J. Lavrakas #MRX

AAPOR… Live blogging from the AAPOR beautiful Boston, any errors are my own…

PaulAAPOR

  • “Applying a total error perspective for improving research quality in the social, behavioural, and marketing sciences”
  • Introduction; He grows orchids, collects movie dvds, and likes sci fi movies. [just as every president should!]  Core values – honesty, integrity, fair, dedicated to family profession and AAPOR
  • Much research is poorly conceptualized and interpreted; most studies could be improved with few if any cost implications
  • Total error approach can help do this, many are unfamiliar with this approach
  • [Yet another Bob Groves mention. this guy must be a hollywood celebrity :) ]
  • “Survey costs and survey errors” 1989, Bob Groves
  • Total error – all problems in a study, all conclusions drawn that are wrong, anything that causes a study to be questionnable or limited in value
  • A way to plan the research, oversee data collection, interpret and disseminate findings, a rigorous process of self-evaluation and improvement
  • Bias – directional error, e.g, too high, too low
  • Variance – nondirectional error, imprecision, lowers confidence
  • Qual and quant researchers need to consider this
  • Representation side of research – have a target population, represent it through a sampling frame, leads to a designated sample the one you start with, end up with a final sample
  • Measurement – start with a construct, operationalize with measurement, gather responses, create a final dataset
  • Put representation and measurement together for final results and conclusions
  • Two top reasons for non-response error- we don’t ask them and they refuse
  • [long chat about different types of measurement error, read your intro to surveys text book]
  • Inferential error: when researchers use inappropriate or wrong analytic tools. Also drawing inferences that aren’t supported by the data
  • Consider terminology that applies to qual and quant – credibility, analyzability, transparency, usefulness
  • Credibility: scope – coverage error, sampling error, unit nonresponse error – external validity; specification error, instrument error, respondent error, interviewer error, construct validity
  • Analyzability: completeness and accuracy of analysis and interpretations, processing error, adjustment error, inferential error, peer debriefing, reflexive journals, triangulation, cause and effect reasoning
  • Usefulness: “do something” with the outcomes, support, refute, refine, generate hypotheses
  • [Reminds me of meta-analysis which only use published data which is generally only the interesting findings not the everyday more common boring findings]
Related articles
May 17 2013

Probability and Non-Probability Samples in Internet Surveys #AAPOR #MRX

AAPOR… Live blogging from beautiful Boston, any errors are my own…

Probability and Non-Probability Samples in Internet Surveys
Moderator: Brad Larson

Understanding Bias in Probability and Non-Probability Samples of a Rare Population John Boyle, ICF International

  • If everything was equal, we would choose a probability sample. But everything is not always equal. Cost and speed are completely different. This can be critical to the objective of the survey.
  • Did an influenza vaccination study with pregnant women. Would required 1200 women if you wanted to look at minority samples. Not happening. Influenza data isn’t available at a whim’s notice and women aren’t pregnant at your convenience. Non-probability sample is pretty much the only alternative.
  • Most telephone surveys are landline only for cost reasons. RDD has coverage issues. It’s a probability sample but it still has issues.
  • Unweighted survey looked quite similar to census data. Looked good when crossed by age as well. Landline are more likely to be older and cell phone only are more likely to be younger. Landline more likely to be married, own a home, be employed, higher income, have insurance from employer.
  • Landline vs cell only – no difference on tetanus shot, having a fever. Big differences by flu vaccination though.
  • There are no gold standards for this measure, there are mode effects,
  • Want probability samples but can’t always achieve them

A Comparison of Results from Dual Frame RDD Telephone Surveys and Google Consumer Surveys

  • PEW and Google partnered on this study; 2 question survey
  • Consider fit for purpose – can you use it for trends over time, quick reactions, pretesting questions, open-end testing, question format tests
  • Not always interested in point estimates but better understanding
  • RDD vs Google surveys – average different 6.5 percentage points, distribution closer to zero but there were a number that were quite different
  • Demographics were quite similar, google samples were a bit more male, google had fewer younger people, google was much better educated
  • Correlations of age and “i always vote” was very high, good correlation of age and “prefer smaller government”
  • Political partisanship was very similar, similar for a number of generic opinions – earth is warming, same sex marriage, always vote, school teaching subjects
  • Difficult to predict when point estimates will line up to telephone surveys

A Comparison of a Mailed-in Probability Sample Survey and a Non-Probability Internet Panel Survey for Assessing Self-Reported Influenza Vaccination Levels Among Pregnant Women

  • Panel survey via email invite, weighted data by census, region, age groups
  • Mail survey was a sampling frame of birth certificates, weighted on nonresponse, non-coerage
  • Tested demographics  and flu behaviours of the two methods
  • age distributions were similar [they don't present margin of error on panel data]
  • panel survey had more older people, more education
  • Estimates differed on flu vaccine rates, some very small, some larger
  • Two methods are generally comparable, no stat testing due to non-prob sample
  • Trends of the two methods were similar
  • Ppanel survey is good for timely results

Probability vs. Non-Probability Samples: A Comparison of Five Surveys

  • [what is a probability panel? i have a really hard time believing this]
  • Novus and TNS Sifo considered probability
  • YouGov and Cint considered non-probability
  • Response rates range from 24% to 59%
  • SOM institute (mail), Detector (phone), LORe (web) – random population sample, rates from 8% to 53%
  • Data from Sweden
  • On average, three methods differ from census results by 4% to 7%, web was worst; demos similar expect education where higher educated were over-represented, driving licence over-rep
  • Non-prob samples were more accurate on demographics compared ot prob samples; when they are weighted they are all the same on demographics but education is still a problem
  • The five data sources were very similar on a number of different measures, whether prob or non-prob
  • demographic accuracy of non-prob panels was better. also closer to political atittudes. No evidence that self recruited panels are worse.
  • Need to test more indicators, retest

Modeling a Probability Sample? An Evaluation of Sample Matching for an Internet Measurement Panel

  • “construct” a panel that best matches the characteristics of a probability sample
  • Select – Match – Measure
  • Matched on age, gender, education, race, time online, also looked at income, employment, ethnicity
  • Got good correlations and estimates from prob and non-prob.
  • Sample matching works quite well [BOX PLOTS!!! i love box plots, so good in so many ways!]
  • Non-prob panel has more heavy internet users
Related articles
May 17 2013

AAPOR Women Leaders Share Their Insights #AAPOR #MRX

AAPOR… Live blogging from beautiful Boston, any errors are my own…

Lessons in Leadership: AAPOR Women Leaders Share Their Insights;

Organizer: Anna Wiencrot, NORC at the University of Chicago
Moderator: Angie Gels, The Nielsen Company
Panelists: Mollyann Brodie, The Henry J. Kaiser Family Foundation Courtney Kennedy, Abt SRBI Nancy Mathiowetz, University of Wisconsin-Milwaukee Eileen O’Brien, Energy Information Administration, U.S. Department of Energy

  • “There’s a special place in hell for women who don’t help other women”
  • “Whatever you are, be a good one”
  • “Big deep breaths”
  • “Do your best, one shot at a time, then move on”
  • (all the panelists have children)  [why does this matter? male leaders don't start a talk by listing off their kids]
  • This is a global phenomenon, and perhaps the US is behind – 17 world leaders in power and mostly in developing countries
  • Women aren’t always taught they can be successful in careers, “not the right time for me”
  • Need to focus on ensuring women are allowed/able to advance
  •  The female brain is wired differently, less aggression, more multitasking/big picture, more gut feeling, more worry
  • Women speak 20 000 words a day compared to men 7000. Female babies make more eye contact. These are untapped skills.
  • Maximize connecting, optimism, big picture thinking, intuition, negotiation
  • Minimize emotion, worry, staying in the background, multitasking, urge to “fix” – You don’t need to be everywhere doing everything

Eileen O’Brien

  • Hang around the people who bring out the best in you, her best teachers were science/math so she hung around them
  • She had thoughts of “the timing isn’t right” but went ahead anyways, also thoughts of “there’s more to this” and pursued the “more” several times
  • If people don’t know you by your first name, then you’re not reaching out
  • Write it down.
  • Bring someone with you who might not get there without your wisdom.
  • It’s okay to be 80% prepared.
  • [sorry, hard to hear this speaker]

Courtney Kennedy

  • Went to an interview that sounded interesting, was asked “have you ever worked with microsoft excel?”, she said yes even though she hadn’t, she got the job a week later, wonders if her entire future hinged on that one answer – she’s not recommending lying :)  You need to take initiative and responsibility for taking yourself to the next level. She bought an Excel for Dummies book on her way home from the interview and spent 3 days learning it
  • Got involved in AAPOR early, introduced to people, felt part of the family in this community
  • A mentor helped guide her, told her to take statistics even though she’d hate it, she would have never done this without him telling her
  • not everyone needs to be quantitative but build your statistical capabilities can open doors professionally, make you more marketable
  • Another mentor let her co-author to get a track record of publications [I like to do this but people are too chicken to take me up on my offers :) ]
  • Geography is important – where you live affects your career, a one career man can move their family and no one thinks of it. A household with two professionals doesn’t work that way. Hard to move back to DC, where she’d love to be now that they are settled elsewhere.
  • Smell the roses.

Mollyann Brodie

  • Careers seem linear and well planned when you look back at them but during the process, they aren’t. Every decision is unclear along the way.
  • Followed interests and passion at each decision point, trusted instinct of what felt like the right fit
  • In grad school, the course track is clear – which courses to take. But she took a path that wasn’t so clear.
  • Try to identify your skills, organization, people person, “committee girl”, managing egos, getting things done, it’s more than being an analyst
  • She is harder on herself than anyone else, don’t let it stop you, assess your own performance as other would, don’t over criticize, give credit where credit is do, don’t be embarrased by your own success
  • There are normally multiple mentors. Those who give you opportunities. Successful people you watch how they act and treat others, you don’t need to have a mentor role to mentor, people are simply watching. Third group of people who make you say I will not do that, and they can be the most powerful shapers.
  • Leaders need to be conscious of challenges of our people to maintain work and family responsibilities, work life balance, be fair and honest about flexibility with the whole team, there is a cost to picking up the slack but it is important to do
  • Managing maternity leaves is the right thing to do even though it is stressful for everyone, you get a conscientious team who know you value them, the work place needs to be more conscious of balancing life so we are more well-rounded
  • Don’t be in such a hurry, there is no rush. You work for a really long time. Worst mistake she made was to end a job and start a new job in another city in a couple of days.
  • Take more vacations.

Nancy Mathiowetz

  • The journey isn’t linear
  • Went to the school where she was beginning her grad degree and asked if they had a job – even though they don’t normally hire newbies. She asked to work for free and they eventually found money for her. Through this she realized she was in the wrong program and switched her Phd program
  • Left school ABD (all but dissertation), 2 years later, an employer gave her 25% of time to finish her Phd
  • Path looks crazy but make opportunities yourself, you don’t need to explain yourself
  • Have a range of mentors
  • Her spouse was very supportive, believed in 50/50
  • Invest in support services you always have care for kids/whomever. One person shouldn’t just automatically stay home.
  • Consider full lives for women AND men. It’s not just kids, it’s aging parents. Maternity you can plan, but a sick parent can’t be planned. Work hard for these policies at your workplace.
  • The right to be at the table comes with the skill set – learn statistics.
  • Lobby at a higher level that allow everyone to have a full integration of their life
  • Have a ten year plan and revisit it every day. Where do you want to sit ten years from now and how do you want to get there. You don’t have to stick to it but consider what you need to do to get to where you want to be.
  • Time is precious, spend it wisely.

Live both the length and width of your life

  • Male leaders don’t necessarily worry about making everyone happy, just move forward at all times
  • Play to your strengths, figure out what they are, ask others what they think your strengths are, you might not recognize what other people naturally see in you
  • Other women business owners face the same challenges, you can be insecure with them if you need to, use them as your support network
  • Honour everyone’s choice, regardless of the path, even people who want to step back from advancement
  • Maybe you don’t play par but you do play through – think about raising kids and your career
  • If something is too hard, maybe it’s just important, you don’t know what is coming so just play through
  • “I never take a vacation in June because that’s when they talk about budget”
  • [Funny audience member asked if she could ask two questions. Don't men just ask 5 questions in a row without asking?  Pardon the extreme stereotyping there. :) Her question was about gumption.]
  • Can you teach people to step up, speak up? [Based on personal experience - absolutely.]
  • Being asked versus volunteering – opportunities often come when people ask you. [ditto, but i put my name out there so much that people remember my name and then they ask me]
  • Mentees sometimes wait until the next meeting to solve a roadblock – just go ahead and start working on a solution now, don’t wait
  • Teach gumption by instilling confidence, many women think they can’t do statistics but yes they can, women should and deserve to be at the table
  • Self-doubt is part of success
  • Not everyone is committed to your success, help people understand this
  • Being assertive and ambitious are masculine and for women to do this means they are being bitchy, but if they don’t, then they are not a leader
  • You can never please everyone, stop worrying that people are saying mean things because you can’t control that
  • “What other people say is more about them than about you” [interesting....]
  • Men can be mean and get away with it but women are just being cranky. Well, no one should be mean.
  • Imposter syndrome – “I don’t deserve to be here” . You did NOT get this far because you are lucky. Tell them why they matter, why they’ve been asked to the table.
  • “Lift as you climb”
Related articles
May 16 2013

The Roles of Blogs in Public Opinion Research Dissemination #AAPOR #MRX

AAPOR… Live blogging from beautiful Boston…

Reg Baker, SurveyGeek

  • First blog post was on randomization
  • His company considered him to be a methodologist because he subscribed to POQ, he kept answering the same questions so he wrote the answers in a blog and referred everyone there
  • Twitter is how you build blog traffic, We love the retweets of our blogs
  • There is a social media bubble of all the people talking about the same things you do, and you meet people around the world only because of your buzz
  • Two families of blogs – those sharing research results and those in the commentator category
  • Biggest peak of all – sarcasm sells – begged people to not use words like disruptive, holistic, superlatives; next largest blog was how to write a mobile pitch piece about the hyperbole around mobile research
  • Conference blogging gets lots of hits, as do posts in a series
  • Hardest thing about blogging is you need to do it all the time and it’s hard, you need to do it day in and day out, something people care about want to hear about
  • Useful and fun way to share information, it can get you into trouble, say things you wish you didn’t say

Annie Pettit, LoveStats

Adam Sage, SurveyPost

  • Put a viewpoint out there to start a discussion
  • Peer reviewed research takes a lot of time
  • Focus on twitter, crowdsourcing, infomatics, concepts that are difficult to publish before they are outdated
  • Blogs consider the readers to be the jury
  • Ripe for innovation, more than just you shouting with a megaphone

Marjorie Connelly, New York Times

  • They post blogs and vet blogs that go on many different places on their site
  • Website has no print deadline so they can post at any time
  • Blogs offer a different voice than the print paper, columnists often have their own blogs and they often use polls to support their arguments – they have no control over those polls
  • Often breaking news or incisive posts
  • Use live blogging for celebrity events like debut of the ipad, Tony Awards
  • Venue for things that wouldn’t be accepted into the paper
  • Let authors say more and more deeply than the printed paper
  • Can do early releases of data in order to tease a later print version

Jeffrey Henning, ResearchScape

  • Started his Vovici blog as part of content marketing, and he needed something to do in the newly formed merged companies
  • First blog post was about asking demographic questions, designed only by considering what google wanted
  • His new company “ResearchScape”  needed the same kind of marketing work
  • His ranking of 50 top blogs turned into 50 days of posts
  • Realized not a lot of people are sharing results of studies – white space in the blogging world to support more
  • Journalists do a poor job of putting research results into context – Jeffrey gives them an F. Researchscape is trying to fix this and Jeffrey gives himself a D for what he’s done so far. He wants to improve to a C+ next year.
  • A blog is a place to practice in a small audience, help you become better at explaining methodologies

Casey Tasfaye, FreeRangeResearch

  • You don’t know your opinion until you write it down
  • Assumptions about what research is changes when you try to write it down
  • Place to combine all her data sources – school, friends, talks – and make sense of it. It’s about her trying to figure things out.
  • Her blogs explores intersections of different worlds, shares discussions about polls, reports events and conferences, things she reads, research findings
  • Her meditation calendar is a good source of  blog posts
  • Good place for problem solving, discuss them in a public way
  • Also talks about digital parenting – how does she deal with her kids and social media
  • Tries to have a blog roll, lists of organizations, lists of helpful links, lists of good tools
  • Twitter is a good tool for listening, amplifying, and discussion
  • very little engagement on the blogs themselves but lots on twitter
  • #WJchat is good to listen to
  • Twitter is a great way to follow conceptual trends
  • A lot of research doesn’t get published and blogging can deal with this
Related articles
May 16 2013

Minimizing Nonresponse Bias (GREAT session) #AAPOR #MRX

AAPOR… Live blogging from beautiful Boston, any errors are my own…

AAPOR Concurrent Session A

Thursday, May 16, 1:30 p.m. – 3:00 p.m.
5 papers on Minimizing Nonresponse Bias (MANY speakers, check the website

First paper

  • Evaluation and Use of Commercial Data for Nonresponse Bias Adjustment
  • Using commercially available data to estimate non-responders, there is a lack of this info
  • RDD is showing increased non-response
  • Census aggregate data is uninformative of nonresponse bias due to error in matching, and low associations with the survey variables
  • Purchased commercial data is better, e.g., filling out your toaster registration card [this is why i NEVER register anything. registering products is ONLY for marketing purposes.]. There can still be lots of missing data, weighting may not be possible, can be high rates of error.
  • Allow the use of incomplete auxiliary data, use multiple imputation
  • They had success matching adults of the same age/gender in the same household

Second paper

  • Interviewer Observations vs. Commercial Data:

    Which is Better for Nonresponse Bias Correction?

  • Should be we budget for commercial data or interviewer observations?
  • How does the quality and usefulness compare?
  • Observer can make a record of a non-responder as they person says “i don’t want to participate”
  • Employment benefits study for social status, family type, house type, foreigners, young people
  • Study tested for observations and commercial data separately and together
  • [Wondering how important this information is given the recent miss on polling in BC Canada]
  • Results show that observer evaluations for unemployment benefits were pretty good, income not so much; Commercial data not so good, worked better for a general population not an unemployed population
  • Can’t say consistently which method was best for predicting employment benefits but commercial data was the worst
  • Make sure the observations are related to the survey topic
  • [cool paper!]
  • Similar costs for both methods

Third paper

  • Assessing the Reliability of Unit Level Auxiliary Data in RDD Surveys: NHTSA Distracted Driving Survey
  • [Why are there different standards of research for gvt research and private research?]
  • Purchased demographic data from a panel company, did a distracted driving survey
  • 18 minute interview [how many responders were just nodding their heads in agreement by the end?]
  • [Funny how we assume there is RIGHT data. Just because you bought or created data doesn't mean it's true.]
  • Landline and mobile surveys differ by 10% in terms of response by the youngest people (20% vs 30%)
  • Across 4 methodologies, demographic frequencies differ by 10% to 40%; match rates between those on multiple datasources as low as 20%
  •  Auxiliary data tend to be household characteristics while interview data tends to be individual characteristics
  • Agreement rates are too low for most measures to facilitate non-response analysis
  • But, auxiliary data might be useful for underrepresented segments

Fifth paper

  • [Awesome ten dollar word title]
  • Comparative Ethnographic Evaluations of Enumeration Methods Across Race/Ethnic Groups in the 2010 Census Nonresponse Follow-up and Update Enumerate Operations
  • Ethnographics were to accompany an interviewer and observe live interviews and tape them if they had permission; to identify issues with enumeration
  • Study targeted a number of race/ethnic groups as well as a control group
  • “No data source is truth”  [ha! that was my side remark further up this page :)  ]
  • Sources of inconsistency are in order are interviewer error, mobility/tenuoousness, respondent concealment/refusal, addressed missed, not in the census, respondent confusion, language barrier
  • 37% of questions were read correctly or with appropriate corrections — two thirds were changed by the interviewer!!!
  • How do you get into apartment buildings? What about occupancy hotels? No buzzer boxes? Unlabeled units? In the middle of nowhere requiring a helicopter to get there?
Related articles
May 13 2013

The new meaning of Above The Fold

In the good old days, above the fold meant making sure people didn’t have to scroll down your website to see the important stuff. Don’t put your brand name down there, don’t put your “buy now” button down there, don’t put the “next page” button down there.
But have you ever thought about above the fold when you’re writing an email? Consider this. Do you open every email to full screen size? I doubt it. Do you open every email? I doubt it.
I live for the preview screen in outlook. If I don’t see something appealing in the subject line or the first line of text in the preview, I just keep moving on.
When it comes to email on my computer, above the fold means one single solitary line of text. Use it wisely. Don’t put your logo there. Don’t put cute graphics there. Put real content words there.
Now think about how you use email on your phone. You definitely don’t open every message and you definitely don’t scroll through every message. So why would you think that everyone else will?
I have a simple message.
Put the good stuff first. Keep it short. Keep it simple. Maybe then I’ll read it.

Written on the go