Extract variable estimates from the SQP 3.0 prediction algorithm

Extract variable estimates from the SQP 3.0 prediction algorithm

get_sqp(study, question_name, country, lang, all_columns = FALSE,
  authorized = TRUE)

Arguments

study

string with the name of the study. Upper and lower cases are ignored and regular expressions are supported.
question_name

A vector of strings specifying the variable names. A search is performed for similar names from all variables in the study. Upper or lower case is ignored and regular expressions are supported.
country

the country where the question was applied in two letter ISO code. See the ISO two letter country name list here for all options. Upper or lower case is ignored.
lang

the language the question should be in, in a three letter character. See the ISO three letter country name list here for all options. Upper or lower case is ignored. This should be a language spoken in country.
all_columns

a logical stating whether to extract all available columns from the SQP 3.0 database. See the details section for a list of all possible variables.
authorized

TRUE to return only the authorized prediction or FALSE to return all available predictions. If set to FALSE a warning is issued reminding the user to pick one prediction for each variable based on the user_id and user_username columns.

Value

get_sqp returns a tibble with the predictions. The number of columns depends on the all_columns argument.

Details

get_sqp is a simple wrapper around find_questions, find_studies and get_estimates for a direct downloading strategy of the SQP data. For a lower-level approach use a combination of these functions to extract SQP data.

SQP predictions can be both 'authorized' predictions, which are performed by the SQP 3.0 software, and 'crowd-sourced' predictions which are added to the database by other users. By default, sqp_data always returns the 'authorized' prediction when it is available. When it is not, it returns the first non-authorized prediction, and so on. If the user wants to choose a specific prediction, then authorized = FALSE will return all available predictions for each question.

If authorized = FALSE and all_columns = FALSE, get_sqp raises an error because there is no way of disentangling which prediction is authorized/unauthorized without the additional user_id column (observed when all_columns = TRUE).

sqp_data returns a four column tibble with the question name and the estimates for quality, reliability and validity. However, if all_columns is set to TRUE the returned tibble contains new columns. Below you can find the descriptionof of all columns:

  • question: the literal name of the question in the questionnaire of the study

  • question_id: the API internal ID of the question

  • id: this is the coding ID, that is, the coding of the authorized prediction

  • created: Date of the API request

  • routing_id: Version of the coding scheme applied to get that prediction.

  • authorized: Whether it is an 'authorized' prediction or not. See the details section

  • complete: Whether all fields of the coding are complete

  • user_id: The id of the user that crowd-sourced the prediction

  • error: Whether there was an error in making the prediction. For an example, see http://sqp.upf.edu/loadui/#questionPrediction/12552/42383

  • errorMessage: The error message, if there was an error

  • reliability: The strenght between the true score factor and the observed variable or 1 - proportion random error in the observed variance. Computed as the squared of the reliability coefficient

  • validity: The strength between the latent concept factor and the true score factor or 1 - proportion method error variance in the true score variance. Computed as the square of the validity coefficient

  • quality: The strength between the latent concept factor and the observed variable or 1 - proportion of random and method error variance in the latent concept's variance. Computed as the product of reliability and validity.

  • reliabilityCoefficient: The effect between the true score factor and the observed variable

  • validityCoefficient: The effect between the latent concept factor and the true score factor

  • methodEffectCoefficient: The effect between the method factor and the true score factor

  • qualityCoefficient: It is computed as the square root of the quality

  • reliabilityCoefficientInterquartileRange: Interquartile range for the reliability coefficient

  • validityCoefficientInterquartileRange: Interquartile range for the validity coefficient

  • qualityCoefficientInterquartileRange: Interquartile range for the quality coefficient

  • reliabilityCoefficientStdError: Predicted standard error of the reliability coefficient

  • validityCoefficientStdError: Predicted standard error of the validity coefficient

  • qualityCoefficientStdError: Predicted standard error of the quality coefficient

See also

sqp_login for logging in to the SQP 3.0 API through R and find_questions, find_studies and get_estimates for the lower-level approach of extracting estimates.

Examples


if (FALSE) {

# Log in with sqp_login first. See ?sqp_login
sqp_login()

# 'es' and 'spa' here stands for Spain and Spanish
get_sqp("ESS Round 4", "tvtot", "es", "spa")


get_sqp(
  "ESS Round 4",
  c("tvtot", "ppltrst", "pplfair"),
  "se",
  "swe"
)

# Sweden-Swedish
get_sqp(
  "ESS Round 4",
  c("tvtot", "ppltrst", "pplfair"),
  "se",
  "swe"
)

# Germany-German
get_sqp(
  "ESS Round 1",
  c("vote", "trstplt"),
  "de",
  "deu",
  all_columns = TRUE
)

}