The majority of the public opinion polling we perform consists of likely voters in New Mexico. We use a dual-frame of landline phones and cell phones to collect the data.
rencontre jeune 17 ans ZiaPoll purchases cellphone and landline data from two main sources. Although we cannot disclose this information, these two list companies are among the leading providers of sampling, data collection and data analytic solutions for survey research.
Our data providers allow us to gather a wireless/mobile sample that reduces the potential of coverage bias by providing a non-overlapping sampling frame that complements their Random Digit Dial telephone sample.
When conducting research concerning public policy issues or political races, it is important to use likely voter models. These models are necessary because a large proportion of those eligible to vote do not end up voting in New Mexico elections.
Likely voters are determined by examining past voting history and voter registration information. ZiaPoll uses various scenarios of past voting history and depending on the election cycle and races being examined. For example, likely voters in a non-presidential year are different than likely votes during a presidential election year.
ZiaPoll public opinion polls are conducted using the following technologies:
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1. Outbound IVR (Interactive Voice Response) technology for landline telephones.
2. Targeted inbound IVR technology for cell phones
Our robo dialing equipment and IVR technology is designed and managed in-house. Landline surveys are completed by making outbound calls to likely voters. Voters have the ability to repeat a question and listen to their options multiple times for clarity. Since cell phones cannot be called using automated dialers, cell phone subscribers are first contacted, and then directed to the IVR technology, so they take the same survey, exactly as those who were dialed on landlines.
Because we randomly select voters from the likely voter database, we call and interview that particular voter so no household selection process is used or needed. Cell phones are overwhelming individual driven as well, therefore no household selection is used or required.
Spanish-speaking interviewers are on staff and surveys are conducted in Spanish should a potential respondent need or requests it.
After all of the interviews are conducted, the combined samples are weighted based on several key factors such as gender, age, education, race, congressional district and landline/cell status. The weights or stratas are determined using our database of likely voters.
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This critical step would not be possible without our extensive database of New Mexico voters. Other pollsters, without this type of internal resource, would be unable to accurately evaluate the demographical profile of New Mexico likely voters. This is why ZiaPoll is able to ensure that the sample as closely as possible reflects the population of likely voters in the state.
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The measurement of sampling error for any particular poll is typically not adjusted for any design effects due to sample weights and/or clustering unless otherwise noted in the release of poll results.
All polls come with a theoretical calculation of sampling error. Most of us are accustomed to hearing phrases such as “plus or minus four percent” when we hear a newscaster citing the most recent poll results. Sampling error, however, isn’t the only error in polling.
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Errors may result from a myriad of other factors and, unfortunately, most of these are impossible to quantify. Factors that can cause errors include:
- Coverage error
- Declined interviews
- Interviewer bias
- Question wording
- Question order
- Imperfect likely voter screening process
click here How does ZiaPoll minimize these errors?
It’s simple and it’s something that sets us apart from our competitors. At ZiaPoll we use our own technology, our own resources, and our own employees to maximize the accuracy of every data collection project we conduct.
We don’t outsource any portion of a polling project – we conduct every aspect of every poll in our offices with employees chosen, trained, and supervised by us.